{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Hybrid Forgetting Curve\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/hybrid_forgetting_curve.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d57aa5df4ed546c6b1fe063e2f1306c2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e6af57f371544ad3a6a558a01fd48a35",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1]\n",
    "\n",
    "def power_forgetting_curve(t, s):\n",
    "    return (1 + t / (9 * s)) ** -1\n",
    "\n",
    "def exponential_forgetting_curve(t, s):\n",
    "    return 0.9 ** (t / s)\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor, i: int) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = power_forgetting_curve(X[:,0], state[:,0]) if i == 1 else exponential_forgetting_curve(X[:,0], state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for i, X in enumerate(inputs):\n",
    "            state = self.step(X, state, i)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = exponential_forgetting_curve(delta_ts, stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.where(seq_lens == 1, power_forgetting_curve(delta_ts, stabilities), exponential_forgetting_curve(delta_ts, stabilities))\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.where(seq_lens == 1, power_forgetting_curve(delta_ts, stabilities), exponential_forgetting_curve(delta_ts, stabilities))\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6f14be97b8424b17a7f6b28d5471ced4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3340\n",
      "Loss in testset: 0.3123\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eee4cd8d20fe400a9090a68908f2585d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.1967, 1.8631, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c5caf97893fa4243b58415a135f0dadb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3316\n",
      "Loss in testset: 0.3100\n",
      "iteration: 15360\n",
      "w: [1.1672, 2.0748, 5.234, -1.3125, -1.1661, 0.05, 1.4782, -0.15, 0.8912, 2.064, -0.1569, 0.3443, 0.9177]\n",
      "iteration: 30720\n",
      "w: [1.1656, 2.0862, 5.3007, -1.7903, -1.4431, 0.05, 1.5374, -0.15, 0.9395, 2.0736, -0.1718, 0.2887, 0.9292]\n",
      "iteration: 46080\n",
      "w: [1.1656, 2.0868, 5.1817, -1.8159, -1.5625, 0.05, 1.5315, -0.1814, 0.9402, 2.0765, -0.1846, 0.3563, 0.8936]\n",
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.2975\n",
      "iteration: 60984\n",
      "w: [1.1655, 2.0868, 5.1751, -1.9236, -1.6545, 0.05, 1.4844, -0.2334, 0.8898, 2.0129, -0.2573, 0.3395, 0.8525]\n",
      "iteration: 76344\n",
      "w: [1.1655, 2.0868, 4.9956, -1.8643, -1.6437, 0.05, 1.5343, -0.1767, 0.9313, 2.0306, -0.2427, 0.2737, 0.8359]\n",
      "iteration: 91704\n",
      "w: [1.1655, 2.0868, 5.0761, -2.0038, -1.7494, 0.05, 1.4925, -0.2313, 0.89, 2.073, -0.2049, 0.3083, 0.7655]\n",
      "Loss in trainset: 0.3168\n",
      "Loss in testset: 0.2971\n",
      "iteration: 106608\n",
      "w: [1.1655, 2.0868, 4.9879, -1.9635, -1.7338, 0.05, 1.5195, -0.2027, 0.9101, 2.0302, -0.2508, 0.3365, 0.6679]\n",
      "iteration: 121968\n",
      "w: [1.1655, 2.0868, 4.9665, -1.9534, -1.7407, 0.05, 1.511, -0.2038, 0.8987, 2.0593, -0.2222, 0.3599, 0.6603]\n",
      "iteration: 137328\n",
      "w: [1.1655, 2.0868, 4.9641, -1.9687, -1.7497, 0.05, 1.5109, -0.1942, 0.8962, 2.0543, -0.2277, 0.3661, 0.6549]\n",
      "iteration: 152688\n",
      "w: [1.1655, 2.0868, 4.9632, -1.9672, -1.7506, 0.05, 1.5054, -0.2006, 0.8905, 2.0491, -0.2331, 0.3609, 0.6507]\n",
      "Loss in trainset: 0.3167\n",
      "Loss in testset: 0.2969\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3202\n",
      "Loss in testset: 0.3395\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "beeadb60b952415a9468df8c8d5dc34f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0404, 2.0717, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1f51eefa8d0649118a60f85afcd84c68",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3171\n",
      "Loss in testset: 0.3380\n",
      "iteration: 15360\n",
      "w: [2.1417, 2.185, 5.1678, -1.3232, -1.2485, 0.05, 1.5585, -0.15, 0.9786, 2.0548, -0.1773, 0.2365, 1.1276]\n",
      "iteration: 30720\n",
      "w: [2.1469, 2.1909, 5.2261, -1.8157, -1.4876, 0.05, 1.5159, -0.1867, 0.971, 2.0311, -0.2246, 0.3727, 1.0917]\n",
      "iteration: 46080\n",
      "w: [2.1471, 2.1911, 5.1051, -1.9872, -1.5017, 0.05, 1.4773, -0.1868, 0.9483, 1.9837, -0.2831, 0.3444, 0.9406]\n",
      "Loss in trainset: 0.3036\n",
      "Loss in testset: 0.3244\n",
      "iteration: 60942\n",
      "w: [2.1471, 2.1911, 5.1071, -1.9152, -1.6869, 0.0647, 1.3834, -0.229, 0.8584, 2.0226, -0.2516, 0.3469, 0.9534]\n",
      "iteration: 76302\n",
      "w: [2.1471, 2.1911, 5.0254, -1.9176, -1.7209, 0.05, 1.3805, -0.204, 0.8614, 2.0164, -0.2614, 0.3741, 0.8686]\n",
      "iteration: 91662\n",
      "w: [2.1471, 2.1911, 4.8593, -1.8528, -1.6706, 0.05, 1.4358, -0.1517, 0.9119, 2.0087, -0.2712, 0.371, 0.807]\n",
      "Loss in trainset: 0.3030\n",
      "Loss in testset: 0.3237\n",
      "iteration: 106524\n",
      "w: [2.1471, 2.1911, 4.8611, -1.9067, -1.6808, 0.05, 1.3962, -0.1859, 0.8663, 2.0244, -0.2553, 0.384, 0.7894]\n",
      "iteration: 121884\n",
      "w: [2.1471, 2.1911, 4.853, -1.9503, -1.7009, 0.05, 1.4069, -0.1708, 0.8747, 2.032, -0.2472, 0.3821, 0.7628]\n",
      "iteration: 137244\n",
      "w: [2.1471, 2.1911, 4.8609, -1.9723, -1.7131, 0.05, 1.3986, -0.1727, 0.8646, 2.0375, -0.2418, 0.3867, 0.7622]\n",
      "iteration: 152604\n",
      "w: [2.1471, 2.1911, 4.8578, -1.9682, -1.7136, 0.05, 1.3968, -0.175, 0.8625, 2.0343, -0.2449, 0.384, 0.7582]\n",
      "Loss in trainset: 0.3030\n",
      "Loss in testset: 0.3236\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3254\n",
      "Loss in testset: 0.3285\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a1b1c795e7a4b7d9d6dfd4f8ede3837",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2245, 1.8688, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1e0fdfd825b64eef90abfc3ae34a043b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3232\n",
      "Loss in testset: 0.3257\n",
      "iteration: 15360\n",
      "w: [1.1548, 1.9619, 5.2298, -1.3102, -1.3283, 0.05, 1.5385, -0.1757, 0.9216, 2.0347, -0.1623, 0.3355, 1.0572]\n",
      "iteration: 30720\n",
      "w: [1.1511, 1.9668, 5.2454, -1.6, -1.5556, 0.05, 1.4748, -0.1824, 0.8803, 1.9446, -0.2634, 0.3379, 0.7362]\n",
      "iteration: 46080\n",
      "w: [1.151, 1.967, 5.1166, -1.8387, -1.5531, 0.05, 1.4924, -0.1728, 0.885, 1.9938, -0.2255, 0.3443, 0.5993]\n",
      "Loss in trainset: 0.3097\n",
      "Loss in testset: 0.3112\n",
      "iteration: 60966\n",
      "w: [1.151, 1.967, 4.9999, -1.6834, -1.673, 0.05, 1.462, -0.199, 0.8458, 2.0383, -0.1934, 0.3669, 0.5347]\n",
      "iteration: 76326\n",
      "w: [1.151, 1.967, 4.9061, -1.7095, -1.6904, 0.05, 1.4406, -0.2128, 0.8186, 2.0297, -0.2058, 0.3266, 0.5462]\n",
      "iteration: 91686\n",
      "w: [1.151, 1.967, 4.8564, -1.7843, -1.759, 0.05, 1.4968, -0.1596, 0.8683, 2.0534, -0.1802, 0.3342, 0.5049]\n",
      "Loss in trainset: 0.3094\n",
      "Loss in testset: 0.3109\n",
      "iteration: 106572\n",
      "w: [1.151, 1.967, 4.8374, -1.8499, -1.7643, 0.0548, 1.5021, -0.1682, 0.8699, 2.0397, -0.1951, 0.334, 0.4367]\n",
      "iteration: 121932\n",
      "w: [1.151, 1.967, 4.8261, -1.8672, -1.7816, 0.05, 1.4875, -0.1876, 0.8531, 2.0369, -0.198, 0.3413, 0.4124]\n",
      "iteration: 137292\n",
      "w: [1.151, 1.967, 4.8389, -1.8944, -1.8014, 0.05, 1.4784, -0.192, 0.8428, 2.0441, -0.1905, 0.3505, 0.4089]\n",
      "iteration: 152652\n",
      "w: [1.151, 1.967, 4.8369, -1.8946, -1.8023, 0.05, 1.4771, -0.193, 0.8412, 2.0423, -0.1924, 0.3506, 0.4078]\n",
      "Loss in trainset: 0.3093\n",
      "Loss in testset: 0.3109\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.4879, 2.0816, 4.8859, -1.9433, -1.7555, 0.05, 1.4598, -0.1895, 0.8647, 2.0418, -0.2236, 0.3651, 0.6055]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,1d,2d,4d,7d,13d,23d,1.3m,2.1m,3.5m,5.5m\n",
      "difficulty history: 0,8.8,8.6,8.4,8.2,8.1,7.9,7.7,7.6,7.5,7.3\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,19d,1.3m,2.4m,4.3m,7.4m,1.0y,1.6y,2.5y\n",
      "difficulty history: 0,6.8,6.7,6.6,6.6,6.5,6.4,6.3,6.2,6.2,6.1\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,2.8m,5.7m,10.8m,1.6y,2.7y,4.5y,7.1y\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,25d,2.2m,5.2m,11.2m,1.8y,3.4y,5.9y,9.9y,15.9y\n",
      "difficulty history: 0,2.9,3.0,3.1,3.2,3.3,3.4,3.5,3.5,3.6,3.7\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6511, 4.8859])\n",
      "tensor([15.8863,  4.8859])\n",
      "tensor([38.4073,  4.8859])\n",
      "tensor([83.6634,  4.8859])\n",
      "tensor([169.9680,   4.8859])\n",
      "tensor([8.8316, 8.2213])\n",
      "tensor([ 2.8746, 10.0000])\n",
      "tensor([4.0732, 9.7443])\n",
      "tensor([5.8598, 9.5014])\n",
      "tensor([8.7450, 9.2706])\n",
      "tensor([13.2651,  9.0514])\n",
      "tensor([19.9465,  8.8431])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,38,84,170,9,3,4,6,9,13,20\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,8.2,10.0,9.7,9.5,9.3,9.1,8.8\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3264, loss after: 0.3096, improvement: 0.0168\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset.loc[dataset['i'] == 2,'p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset.loc[dataset['i'] > 2,'p'] = exponential_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset.loc[dataset['i'] == 2,'p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset.loc[dataset['i'] > 2,'p'] = exponential_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9284\n",
      "RMSE: 0.0189\n",
      "[0.0978406  0.89146502]\n"
     ]
    },
    {
     "data": {
      "image/png": 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D0mq1UlpamuTk5CTFx8dLa9eulTp16iRJkiTt2rVLAqQbN25I2dnZkru7u3TgwIE844waNUp64YUXJEmSpN27d0uAlJKSIkmSJA0ePFh64okn8uw/dOhQycfHx/x8+vTpkru7u5SWlmbe9u6770pt2rQxP+/cubP05ptv5hln1qxZUs+ePfNsu3HjhgRIkZGRUnp6uqRUKqVff/3V/HpSUpLk5uaWb6zcrFq1Ks/6cvPvv/9K3t7eUnZ2dp7tderUkZYtW1bomE2aNJG++eYbSZIk6ffff5e8vb3znG9uCjrXgli4cKHk7u4ueXl5SV27dpU++ugj6erVq+bXly1bJlWpUkXKysoyb1uyZIkESCdPniz0XP/44w+puI/V3OcjSZJUs2ZNacCAAXn2efnll6Xhw4dLer3evO3ff/+V5HK5lJWVVex1uB/Te8vDw0Py8PCQMOY+SU899ZR5n1GjRkljxozJc1zuOSMjIyVAOnr0qPn1y5cvS4D05ZdfmrcB0ltvvZVnnG7dukmffPJJnm0//vijVLVqVUmSJOmLL76Q6tevL2k0mnxrt+aeX7p0SQKk/fv3m19PTEyU3NzczO/lVatWSYB05coV8z6LFi2SgoODCxw/IyNDOnbsmMXX+kEiKSlJ+uD7v6VZvx0u8vHBNz9IiR/VlaTp3lLW9CrS5KmTpJqT/5Sqvb9UGrNusaTR5b+vthAVFSUB0s2bN+0yXmVHlIERFIvJBRweYLQAVilHLuCyokuXLmRkZHD06FFSUlKoX78+gYGBdO7cmZEjR5Kdnc2ePXuoXbs2NWrU4Ny5c2RmZtKjR48842g0Glq2bFngHBcvXmTgwIF5tj366KNs3rw5z7bw8PA8MVBVq1Yt0CqTm1OnTrF79248PfO3wbt69SpqtRqNRkObNm3M2/39/WnQoEGR4xY3p0qlytf1JSsry5wko1KpmDFjBlu2bCEmJgadTkdWVpbZYtajRw9q1qxJ7dq16d27N71792bgwIFWFxMfN24cw4YNY8+ePRw6dIh169bxySefsGnTJnr06EFkZCTNmzfP0yWmXTvr+5MWdz4mHn744TzPT58+zenTp/OECEiShMFgICoqyubr8O+//+Lu7s6hQ4f45JNPWLp0qfm1U6dOcfr0adasWVPgnJcuXcLJyYlWrVqZX69bty5+fvktOvefz6lTp9i/f38eC7Zeryc7O5vMzEwGDRrEggULzOfTt29f+vXrh5OTk1XnGhkZiZOTU573bZUqVWjQoAGRkZHmbe7u7nnici35m6msuHp44eHtW/CLkgHpxkG4tguZcxxXXKoxTjuBc7jiH/Qna4e+SdNgUdevvCIEoKBYzDUA73MBJ2dq0OkNOCnsF0ng7uyOaorK4v0TVGpi72bh566kup91IuBSXBpqnYHaAZ54uDjh7mz58XXr1qV69ers3r2blJQUOnfuDEBoaChhYWEcOHCA3bt38/jjjwNGIQCwZcsWqlXLW+fKxcXFqnXfj7Nz3iBqmUyGwWAoZG/M6+nXrx+fffaZeZup/2y9evW4du1aidZU2Jz3x06aMMXSvfPOO+zcuZN58+ZRt25d3NzcePbZZ82JCl5eXpw4cYI9e/awY8cOpk2bxowZMzh69KjV2cdeXl7069ePfv36MXv2bHr16sXs2bPzifTCkMvl+cIG7k94KO58THh4eOR5rlKpGDFiBG+//Xa+VnA1atRAqVTadB1q1aqFr68vDRo0ID4+nsGDB7Nv3z7znK+++mqe2Lvcc166dKnYa1LU+cycOZOnn346376urq6EhYVx8eJF/v77b3bu3Mnrr7/O559/zt69e+16z00U9Ddz/70UFINGRdbpjbipbgISm/RtmaMZTIJyK5N7tOedDotRyEVmb3lGxAAKikSrN3ArJQsw1gAE8HdXIpMZs2dTMu2b4SeTyfBQelj8cHVyx93ZA0+lp1XHGR+euDt74O7sjofSw+rs265du7Jnzx727NmTp/xLp06d+Ouvvzhy5Ig5/q9x48a4uLgQHR1N3bp18zwKilMDY7LJ0aNH82y7/7klKJXKfLFurVq14ty5c4SHh+dZS+3atfHw8KBOnTo4Oztz+PBh8zEpKSlWiYD7adWqFbGxsTg5OeW7BgEBAYAx7nHEiBEMHDiQZs2aERISki+Rw8nJie7duzN37lxOnz7N9evX+eeffwo9V0uQyWQ0bNjQnPDQqFEjTp8+nSejO3dyDxhjCdPT0/MkSZgSRExYcj4F0bJlSy5evJjvOtWtW9ccs1fUdbCEcePGcfbsWf744w/AeH/Onz9f6JwNGjRAp9Nx8uRJ8xhXrlwhJSWl2LlatWpV6PmYBK6bmxv9+vXj66+/Zs+ePRw8eNBcpsbSc23UqBE6nS7P+zYpKYmLFy/SuLGwRNmLpFuXyD74HW6qm2hR8I+hKRMkT/zq/MiBCR8zuePb5Ub87du3j379+hEaGopMJmPDhg15Xs9dHin34/PPPzfvEx4enu91U5y1idOnT9OxY0fzD5q5c+fmW8u6deto2LAhrq6uNGvWjK1btzrknC1FWAAFRXIzORO9QcLNWUGwt9FS5aSQ4++uJClDQ6JKTaBXySxYJcHWLGDAXAnQ2ixgE127dmXcuHFotVqzBRCgc+fOjB8/Ho1GYxaAXl5evPPOO0ycOBGDwcBjjz3G3bt32b9/P97e3gwfPjzf+G+88QadOnVi/vz59OvXj3/++Ye//vrLaqEaHh7O4cOHuX79Op6envj7+zNu3Di+/fZbXnjhBd577z38/f25dOkS//d//8fq1avx9PRk1KhRvPvuu1SpUoWgoCA++OCDfNaogtDr9fmEkIuLC927d6ddu3YMGDCAuXPnUr9+fe7cucOWLVsYOHAgDz/8MPXq1WP9+vX069cPmUzG//73vzzWzM2bN3Pt2jU6deqEn58fW7duxWAwmF3TBZ3r/WuOiIhg+vTpvPTSSzRu3BilUsnevXtZuXIlkydPBmDIkCF88MEHjB49milTpnD9+nXmzZuXZ5w2bdrg7u7O1KlTmTBhAocPH2b16tV59inufArjvffeo3379rzxxhuMHj0aDw8Pzp8/z86dO1m4cGGx18ES3N3dGT16NNOnT2fAgAFMnjyZtm3bMn78eF555ZV8czZs2JDu3bszZswYlixZgrOzM2+//TZubm7FvienTZvGk08+SY0aNXj22WeRy+WcOnWKs2fPMnv2bFavXo1erzdf0//7v//Dzc2NmjVrWnWu9erVo3///owePZply5bh5eXF+++/T7Vq1ejfv7/F10ZQMMmqbBLO/kP97NPIgCTJiz+kIGKdzvNej1ZM6TGl3Ag/ExkZGbRo0YKXX365QAv0/dnff/31F6NGjeKZZ57Js/2jjz5i9OjR5ue5w27S0tLo2bMn3bt3Z+nSpebkJ19fX3NW/4EDB3jhhReYM2cOTz75JGvXrmXAgAGcOHGCpk2b2vOULadsQxBLH5EEYh27ImOlmpM3S72+zJvw0WP+Hqnm5M3SvkvxNo9dUBKItUQnZUinbqZIcXezit/5Pi7HpUunbqZIqZlqm+Y2BSQ3bNgwz/br169LgNSgQYM82w0Gg7RgwQKpQYMGkrOzsxQYGCj16tVL2rvXeG3vTwKRJElavny5VK1aNcnNzU0aMGCANHv2bCkkJMT8+vTp06UWLVrkmefLL7+UatasaX5+8eJFqW3btpKbm1ue9/6lS5ekgQMHSr6+vpKbm5vUsGFD6bXXXpN0Op0kSZKUnp4uvfjii5K7u7sUHBwszZ07t9gkC1OA/f2POnXqSJJkvOdvvPGGFBoaKjk7O0thYWHS0KFDpejoaPM17dq1q+Tm5iaFhYVJCxcuzDPnv//+K3Xu3Fny8/OT3NzcpObNm0u//PJLseeam4SEBGnChAlS06ZNJU9PT8nLy0tq1qyZNG/evDxJFwcPHpRatGghKZVK6aGHHpJ+//33PEkgkmRM+qhbt67k5uYmPfnkk9Ly5cvzJIEUdz6SZEwCyZ1EIUmSpNfrpV27dkndu3eXPD09JQ8PD6l58+bSxx9/bNF1uJ+C3luSJEnR0dGSk5OT+dgjR45IPXr0KHBOSZKkO3fuSH369JFcXFykmjVrSmvXrpWCgoKkpUuXmvcBpD/++CPfGrZt2ya1b99ecnNzk7y9vaVHH31UWr58ufk6tmnTRvL29pY8PDyktm3bSn///bdF53r/9UxOTpZeeuklycfHR3Jzc5N69eolXbp0yfy6tck7lT0JZNZvh6WPt5yXnl2wTZo05T1p/tSR0vypI6URU96WAqeOkpp+Nlma9H/bpKSkJIevp6RJIIW9N3PTv39/6fHHH8+zraC/0dwsXrxY8vPzk9Tqe98lkydPzvMd8Nxzz+VL6mvTpo306quvWn4CdkYmSZUr8OHWrVuEhYURFRVFeHh4WS+n3LPivyhmbT5Pn6YhLHmxtXn7kG8PceBqEl8ObsHAltVtGjs9PZ1Lly7RqFEjq4P4TdxIyuBulpZQXzdzhxJLuZagQqXWUcPfHV93pU3zlzajR4/mwoUL/Pvvv3Yf22AwkJaWhre3t0WWvsrG9evXqVWrFidPnnR4+72Kci9Mn6d///033bp1K+vlOITMzEwiIyOpX79+pSs4HROfwJs/nSQx/jbdOII7arTI2YycSIWax2t1o021R8lMT+P1rnXx9/d36HpMf4Pnz5/PE0vt4uJiUSy1TCbjjz/+YMCAAQW+HhcXR/Xq1fn+++8ZMmSIeXt4eDjZ2dlotVpq1KjBkCFDmDhxIk5ORifqsGHDSEtLy+NeNsWAJycn4+fnR40aNZg0aVKempXTp09nw4YNeWqhlibCBSwokuv3ZQCbMImtpDLuB6zP8d9a2wkEsLkQdGkyb948evTogYeHB3/99Rfff/89ixcvLutlCSop//zzDyqVimbNmhETE8N7771HeHi4VTUIBeUfSZLYdjaWj387SNDdUzzpcRMZEIecX8nG0zeMsQ2ewt+tSrFjOYL74zmnT5/OjBkzSjzu999/j5eXVz5X8YQJE2jVqhX+/v4cOHCAKVOmEBMTw/z58wGIjY2lVq1aeY4JDg42v+bn50dsbKx5W+59YmNjS7xuWxECUFAkpgzgWlUKFoAJZVwKxiTe5DY0EDcdUp6N4EeOHGHu3Lmkp6dTu3Ztvv76a1555ZWyXpagkqLVapk6dSrXrl3Dy8uL9u3bs2bNmnxZtYKKy+lbqczeHEn09cvM0i/gsLwRMlw4hp5/5Ho61+7Fo9UfRUbZtawsyAJoD1auXMnQoUPzlH8CmDRpkvn/zZs3R6lU8uqrrzJnzhy7zV0WCAEoKJL7awCaqOJZPvoBl8gCSPm3AP76669lvQRBDuHh4eX6x0Jp0KtXL3r16lXWyxA4gJi7WXy+7SLrT96mi/wkf7ksQcpO5199Q7aiJcM3jFcaPIW/m2PdvJbg5eWFt7e3Xcf8999/zX3Bi6NNmzbodDquX79OgwYNCAkJIS4uLs8+puchISHmfwvax/R6WVB+g0sEZY5ap+dOqrEETHhA3hi9QM/yUQzakPOFbEspQpNmlKjcX+oCgaDykqHWMX/HRbrO28Omkzd432ktq5Wf4ydTEYGeNQqJmvV6Mfyh4eVC/DmKFStW0Lp1a1q0aFHsvhEREcjlcoKCggBjkfh9+/blqQO6c+dOGjRoYC6U3q5dO3bt2pVnnJ07d9pUYN5eCAugoFBuJmdikMBDqTALPhOO7AdsDeYyMDZYAO+5gO25IoFAIKgYnLl1l9fWHOdWShbVSGCF5yIa6oy1Pr9GzfrqLXnafwShQbWKGan8olKpuHLlivl5VFQUERER+Pv7U6NGDcBYxmXdunV88cUX+Y4/ePCguae7l5cXBw8eNPdxN4m7IUOGMHPmTEaNGsXkyZM5e/YsX331FV9++aV5nDfffJPOnTvzxRdf8MQTT/Dzzz9z7Ngxli9f7uArUDjCAigolKjETMDo/r2/zpcpBrAsXcCSJKGXTHUAS5IEIhSgQCCoPEiSxNrD0Tyz5AC3UrIY7HWaHR7v01B3iVQkhjjpUfT9gt+G/ImPa/5WfxWJY8eO0bJlS3PLzUmTJtGyZUumTZtm3ufnn39GkiReeOGFfMe7uLjw888/07lzZ5o0acLHH3/MxIkT8wg3Hx8fduzYQVRUFK1bt+btt99m2rRp5hqAAO3bt2ft2rUsX76cFi1a8Ntvv7Fhw4ayqwGIsAAKiqCwDGCAKqYs4Aw1kiRZXZzYHuQWbrZlARv/FfpPIBBUFrI0ej7YcIb1J27jjI4lAevoo/oTgCPo+bJ6cz5+5v+o7Veb5OTkMl5tyenSpUuxsbtjxozJI9Zy06pVq3xdgAqiefPmxZbnGjRoEIMGDSp2rNJCCEBBoUQVkgEMUMXD6ALW6iXuZmnLpI6ePqehgrE1j/XHm0RrZQ/sFwgElYNrCSpeX3OCC7Hp1JTFscr7S2qrogH4Wm7Apdcc1jw6DrlMOAcrA0IACgqlKAugq7MCL1cn0rN1JKo0ZSIAzQkgMmyyQJo+4spzFrBAIBDYg21nY3hn3WlUah3Puh1jBl/jqdaRjMT84Hq88sLvhPuGl/UyBaWIkPmCQjEJwFoBBXfpKOtMYL3B9vg/yGUBtNuKyg8FNT13BKtXr8bX19f8fMaMGXm6ZIwYMaLQqvuOIjw8nAULFpTqnAJBeUWrN/DxlvOM/b8TaNWZzPP8lnnSfDwlHYdkElu7TWHW2GNC/FVChAAUFEi2Vs+du9kAhBfgAoZctQDLSADeswDaJgDtUQj64MGDKBQKnnjiCauPLWuhEhsbyxtvvEHt2rVxcXGhZs2aPP/88/lKFVjDO++8U6LjreF+8Wni6NGjhcbzCASVibi0bIZ8e4hv/40iXBbDH27v8qxuNwA/+4QQMv44L3acUiYx3IKyR7iABQVyI8mYAezl6oS/R8Hu3XuZwBXcAlgCE+CKFSt44403WLFiBXfu3CE0NNT2wUqR69ev06FDB3x9ffn8889p1qwZarWaTZs28cYbb3DhwgWbxvX09MTT07NEa9NoNCiVtocUBAYGlmh+geBB4ODVJN746QSJKg0Dnf9jpmIp3pKBRCSOPvoKg/t8IYRfJUdYAAUFEmV2/+YvAWPC3A84o2xKwZTUAmg6zNYyMCqVil9++YXXXnuNJ554gtWrV+fb588//+SRRx7B1dWVgIAABg4cCBgz027cuMHEiRNzkliMi7nfhQqwYMECwsPDzc+PHj1Kjx49CAgIwMfHh86dO3PixAmr1v76668jk8k4cuQIzzzzDPXr16dJkyaMGzeOAwcOmPebP38+zZo1w8PDg7CwMF5//XVUKlWh4xa0foCZM2cSGBiIt7c3Y8eORaO5957p0qUL48eP56233iIgIMDcaaKouffs2cPIkSO5e/eu+fqZeoHeb1mNjo6mf//+eHp64u3tzXPPPZenIr9pzT/++CPh4eH4+Pjw/PPPk56ebtU1FQjKAwaDxOI9Vxj63SHSVSrmuHzDl4rFeGPgjKsX6tG76NN3vhB/AiEABQVj6gFcmPsXclkA7egCliSJTI3OoocqW0+2Vo9aZ7D4mNyPbI3x+EyNnkyNzmpX8K+//krDhg1p0KABL774IitXrswzxpYtWxg4cCB9+/bl5MmT7Nq1i0cffRSA9evXU716dT766CNiYmKIiYmxeN709HSGDx/Of//9x6FDh6hXrx59+/a1WLAkJyezbds2xo0bh4dH/vub260ql8v5+uuvOXfuHN9//z3//PMP7733nsVrBdi1axeRkZHs2bOHn376ifXr1zNz5sw8+3z//fcolUr279/P0qVLi527ffv2LFiwAG9vb/P1e+edd/LNbTAY6N+/P8nJyezdu5edO3dy7do1Bg8enGe/q1evsmHDBjZv3szmzZvZu3cvn376qVXnKRCUNXeztIz58Rhzt12kFrf5w2USL8gOYkDiZP3uNH03imrVHinrZQrKCcIFDGVWx648U1QGsAlTDGCCHYtBZ2n1NJ623W7jWcP5j3rhrrT8T2LFihW8+OKLAPTu3Zu7d++yd+9eunTpAsDHH3/M888/n0fsmNoM+fv7o1Ao8PLysroX5OOPP57n+fLly/H19WXv3r08+eSTxR5/5coVJEmiYcOGxe771ltvmf8fHh7O7NmzGTt2LIsXL7Z4vUqlkpUrV+Lu7k6TJk346KOPePfdd5k1axZyufE3aL169Zg7d67FcyuVSnx8fJDJZEVev127dnHmzBmioqIICwsD4IcffqBJkyYcPXqURx4xfhkaDAZWr16Nl5cXAC+99BK7du3i448/tvg8BYKyJC1by9DvDnH2dhoDFXuZ5fQtnjIDKQpntP0X0rL582W9REE5o1JbAI9EJdN7wT5GrDpa1kspd0QVkwEMjrEAVhQuXrzIkSNHzJXjnZycGDx4MCtWrDDvExERQbdu3ew+d1xcHKNHj6ZevXr4+Pjg7e2NSqUiOjraouOtsXT+/fffdOvWjWrVquHl5cVLL71EUlISmZmZFo/RokUL3N3vvY/atWuHSqXi5s2b5m2tW7d2yNyRkZGEhYWZxR9A48aN8fX1JTIy0rwtPDzcLP4AqlatSnx8vMXzCARlSaZGx8hVR7h6O57PnL/hS+dleMoM3Amoi++bZwgS4k9QAJXaAujmrOBCbDoJZZTEUJ6xxAUc6IB+wG7OCs5/1MuifW8nZ5GSpSHYy5VAb5fiD7iPDLWOqMQMXJwU1Av2xM1ZYfGxK1asQKfT5Un6kCQJFxcXFi5ciI+PD25ublavSS6X5xNouRuMAwwfPpykpCS++uoratasiYuLC+3atcsTV1cU9erVQyaTFZvocf36dZ588klee+01Pv74Y/z9/fnvv/8YNWoUGo0mj6grKfe7oktzbgBnZ+c8z2UyGQaDwa5zCASOQK3T8+KKvaRHX2GD8ksayGPQA6p24wjtMQvkln+uCSoXldoCWDfIE5nMmMRQGa1YhZGp0RGXZrwetYpwATuiH7BMJsNd6WTRQ+ksx9VZgYerZfvf//BwccLVWYHSSY670sniMACdTscPP/zAF198QUREhPlx6tQpQkND+emnnwBja6CiSqIolUr0en2ebYGBgcTGxuYRgREREXn22b9/PxMmTKBv3740adIEFxcXEhMTLbzCRvdzr169WLRoERkZGfleT01NBeD48eMYDAa++OIL2rZtS/369blz547F85g4deoUWVlZ5ueHDh3C09Mzj1XufiyZu6Drdz+NGjXi5s2beayN58+fJzU1lcaNG1t9LgJBeSJbq6HX1z9T59Y2Nik/pIE8hkwXb+TD/8Sn1ydC/AmKpFILQDelgpr+RkvCpViR8WfieqLRxebr7lxkhw9TP+AsrZ4Mta5U1pYbUwcP27OAbSsDs3nzZlJSUhg1ahRNmzbN83jmmWfMbuDp06fz008/MX36dCIjIzlz5gyfffaZeZzw8HD27dvH7du3zQKuS5cuJCQkMHfuXK5evcqiRYv466+/8sxfr149fvzxRyIjIzl8+DBDhw612tq4aNEi9Ho9jz76KL///juXL18mMjKSZcuW0aFDBwDq1q2LVqvlm2++4dq1a/z444/mBA1r0Gg0jBo1ivPnz7N161amT5/O+PHjzfF/BWHJ3OHh4ahUKnbt2kViYmKBruHu3bvTrFkzhg4dyokTJzhy5AjDhg2jc+fOPPzww1afi0BQXjgdd4Z2n37ChJS1fO68HDeZhuya7XF/4wSyWp3KenmCCkClFoAA9YONcT8X44QANJG7BExReCgVuDob30JlYUEtaR1A05vf2uzfFStW0L17d3x8fPK99swzz3Ds2DFOnz5Nly5dWLduHZs2beKhhx7i8ccf58iRI+Z9P/roI65fv06dOnXMtesaNWrE4sWLWbRoES1atODIkSP5sltXrFhBSkoKrVq14qWXXmLChAkEBQVZdQ61a9fmxIkTdO3albfffpumTZvSq1cv9u7dy6JFiwBj7N78+fP57LPPaNq0KWvWrGHOnDlWzQPQrVs36tWrR6dOnRg8eDBPPfWUuWRLYVgyd/v27Rk7diyDBw8mMDAwXxIJGEX+xo0b8fPzo1OnTnTv3p3atWvzyy+/WH0eAkF5QKvXMnvvx7yx8FN+0/7M04r/0CNHenwarsO3gKeogymwDJlUkjYIFZBbt24RFhZGVFQU4eHhfLHjIt/8c4UXHg1jztPNy3p55YJFu6/w+faLPN2yGvMHP1Tkvo999g+3UrL4/bX2tK7pZ9U86enpXLp0iUaNGtkU03UpNp1snZ7aAR54ujoXf8B9aHQGLsSmIZPJaFYtv5irbBgMBtLS0vD29i7SOidwPOJelB8yMzOJjIykfv36eRKFyoIzcWcYsWE4nW558an8HC4yLRkugXgM+RFqtrP7fMnJySzefQUPb98i98tIS+X1rnXx9/e3+xpyc/36dWrVqsXNmzepXr26Q+eqDFT6TxazBVC4gM1EWVACxkRZZgLrpZJ2AjH+K0lSidrBCQQCgSPR6rXM3jebLstaM/V2Bl8qInCRabkd2BGPCYcdIv4EDz6VOgsYoEGIUQBeilOJeoA5WFID0ERAGfYDNhjs0wsYjHGA4tYLBILyxum404zYMAJiTnFYCqCuPBatpOB4vTdoO2Q6CAuxwEYq/TsnvIoHzgoZKrWOO3ezy3o55QJTCZhaRZSAMeGITGBLkCTJDhbAe8dJCAugQCAoP2j1Wj7a+xEPL3uY9jFnOYgXdWXZ3JIC+K35Mtq+OFOIP0GJqPQWQKWTnNoBnlyMS+dSbDrVfK2v3fYgkZ6tJVFlFHPhRRSBNnGvH3DpWgANufSazVnA940nCiYIBILyQERsBCM3jiQqJoKfcOMZnAGJnfrWnGj1Me8NaFvWSxQ8AIifD0D9EJEJbMJUAibAU4mXBYkVZeUCNrl/Zchsdt3KZDKbS8EIBAKBvdHoNczYM4NHvn0E55jTnJJ58wzOaCQFM7UvsaPZfN7t31aEKgnsQqW3AAI0CPbkT8pvLcBsrR6lQm6zq9MaoizoAJKbKmXkAr7n/qVEH4ZyQI/1pWAEAoHAnpyMOcnIjSM5FXuKt1AyFw+cJYmbUhDjNG8Q1vQxvn62Ral8DwgqB8ICyL1M4Evx5U8Axqdl88jHf/PamuOlMp81CSBQdlnAJU0AMWESj6Lpl0AgKAs0eg3Tdk/j0e8eJTr2FFsVPnyJK85IbNU/yhPqj/Gv35YvBz+EQog/gR0RFkDuZQJfjlOhN0jl6o/snwvxpGfrOH4jtVTmu25hEWgTpn7ApS0AS5oAYiJ3KRiBQCAoTU7EnGDEhhGciT9DW0nBJqcgAnXZaCQnPtK9xK+ynrzRox6vdq6D0knYawT2RQhAIMzPHVdnOdlaA9HJmRaLn9Lg4LUkgFJrtWatC9hkAUzL1qHW6XFxKp1UCntZAOUiBlAgEJQyap2a2ftmM+e/ORgMemY4+/E/rYRcl02UIZjx2jfxqd2a7QOblavvI8GDhfhJgdGKVC+o/BWEliSJg1eNAjBLqze3PnMk91zAlnXm8HZ1xinHCpekKr04QH3OpbCXBdBQjhTgjBkzCA4ORiaTsWHDhrJejtXs2bMHmUxGamoqAKtXr8bX19f8+owZM3jooYdKdU1dunThrbfeKtU5BYKCOHbnGA9/+zCz/52Nr8HAMY+6TNfqkWNgk74dw5w+Z9Sg/qx5pY0QfwKHIgRgDuY4wHKUCXwtMYP49Huu1QyNY62AdzO1pGRqAcstgHK5jCplkAmst1sMoPFfa/XfiBEjzFnESqWSunXr8tFHH6HTleweRUZGMnPmTJYtW0ZMTAx9+vQp0XhgneBKS0vjww8/pGHDhri6uhISEkL37t1Zv369zW7ywYMHc+nSJZuOtZb7xaeJ9evXM2vWrFJZg0BQEGqdmg92fUDb79pyNv4sTyqrcNW5Bq0y4smWnHlf+wr/Nf+UTW/34elW1UWmr8DhCBdwDg1CPIHyVQrGZP0zkaHW4W1Dz1tLMbl/g7xc8HCx/K0R4OlCXJq6VC2AhlxZwCVBjskFbL246d27N6tWrUKtVrN161bGjRuHs7MzU6ZMsXosvV6PTCbj6tWrAPTv37/UvwBSU1Pp1asXKpWK2bNn88gjj+Dk5MTevXt57733ePzxx/NY8izFzc0NN7eS1dfUaDQolUqbj3d0j1KBoCiO3j7KyI0jOZdwDpkE/1elPS8knUdOClcNVZnj+T6vPNuPtrWrlPVSBZUIYQHMwWwBLEcu4EPX8gtAR2JtBrAJUxxgQilaAM0xgPZyAdtwrIuLCyEhIdSsWZPXXnuN7t27s2nTJgDUajXvvPMO1apVw8PDgzZt2rBnzx7zsSa36KZNm2jcuDEuLi68/PLL9OvXDwC5XJ5HAH733Xc0atQIV1dXGjZsyOLFi/Os5datW7zwwgv4+/vj4eHBww8/zOHDh1m9ejUzZ87k1KlTZovl6tWrCzyfDz74gJs3b3Lw4EGGDx9O48aNqV+/PqNHjyYiIgJPT+OPpB9//JGHH34YLy8vQkJCGDJkCPHx8YVep/tdwCaWLVtGWFgY7u7uPPfcc9y9e9f82ogRIxgwYAAff/wxoaGhNGjQoNi5r1+/TteuXQHw8/NDJpMxYsQIIL8LOCUlhWHDhuHn54e7uzt9+vTh8uXL+da8fft2GjVqhKenJ7179yYmJqbQ8xQI7idbl82Uv6fQdkVbziWco4lbCOc82jM06SxyDGwwdGRbh59ZNOklIf4EpY6wAOZgygSOSswo1WSGwpAkiUPXkvNsU6n1Dp0zKtHyFnC5sasLWJJAm1nsbgZNFjKtBrlODxrbi7godFnItFoktQRuziVqCOzm5kZSklG0jx8/nvPnz/Pzzz8TGhrKH3/8Qe/evTlz5gz16tUDIDMzk88++4zvvvuOKlWqULVqVbp06cLIkSPzCI01a9Ywbdo0Fi5cSMuWLTl58iSjR4/Gw8OD4cOHo1Kp6Ny5M9WqVWPTpk2EhIRw4sQJDAYDgwcP5uzZs2zbto2///4bAB8fn3xrNxgM/PLLLzz77LOEhobme90k/gC0Wi2zZs2iQYMGxMfHM2nSJEaMGMHWrVstvlZXrlzh119/5c8//yQtLY1Ro0bx+uuvs2bNGvM+u3btwtvbm507d1o0d1hYGL///jvPPPMMFy9exNvbu1DL44gRI7h8+TKbNm3C29ubyZMn07dvX86fP4+zs7P5/sybN48ff/wRuVzOiy++yDvvvJNnjQJBYRy+dZiRG0cSmRgJwPTq/Zhw6zT+0lmyJCWr/cbTc8gkBuTEnwsEpY0QgDmEeLvi5epEeraOqMQMGoZ4l+l6rsSrSFSpcXGSE+rrRlRihuMtgEm2WQAD7VkMWpsJn+QXIPdTLedRUmrmfjL1DiitD7qWJIldu3axfft23njjDaKjo1m1ahXR0dFmMfXOO++wbds2Vq1axSeffAIYxczixYtp0aKFeSyTpSwkJMS8bfr06XzxxRc8/fTTANSqVYvz58+zbNkyhg8fztq1a0lISODo0aNmV2fdunXNx3t6euLk5JRnzPtJTEwkJSWF+vXrF3u+L7/8svn/tWvX5uuvv+aRRx5BpVLlEYpFkZ2dzQ8//EBAUAgymYxvvvmGJ554gi+++MK8Tg8PD7777rs8rt/i5jadf1BQUKHuapPw279/P+3btweMIjssLIwNGzYwaNAgwHh/li5dSp06dQCjqP/oo48sOj9B5SVbl8303dOZd3AeBslAVfcgNlXtTasrG5EjcZXqXO6yiLFdOos4P0GZIgRgDjKZjAbBXhy7kcLF2PQyF4Cm8i8Ph/uRqTFa/lSl5AKuZWEGsImy6gdc1mzevBlPT0+0Wi0Gg4EhQ4YwY8YM9uzZg16vzyem1Go1Varcc/MolUqaN29e5BwZGRlcvXqVUaNGMXr0aPN2nU5ntuRFRETQsmXLEsW5WRMDefz4cWbMmMGpU6dISUnBYDBaYKOjo2ncuLFFY9SoUYOQqqFExqShkMto27YtBoOBixcvmgVgs2bN8sX92WPuyMhInJycaNOmjXlblSpVaNCgAZGRkeZt7u7uZvEHULVq1SJd3QLBoVuHGLlxJBcSLwAwrtGzzE5KwffKBgC2OnWn+ehl9A4OKMNVCgRGhADMRf0QowAsD5nApgSQdrWrcDjK6Ap2pAVQkiSzC9jqGEB7FoN2djda4orhakIGmRodNfzd8HGzPTngdkoWyZkagr1dCHK2Tvh27dqVJUuWoFQqCQ0NxcnJ+OekUqlQKBQcP34chSJvKEFuC5mbm1uxFgCVSgXAt99+m0ewAOaxS5pgARAYGIivr2+x2boZGRn06tWLXr16sWbNGgIDA4mOjqZXr15oNNZZgLV6AwZJwqCXCixx5OGR931oz7ktweQKNiGTyUTBcEGBZGmzmLZ7GvMPzccgGQjxDGF96/G0PrQCZXYSGZILy7zGM3zsZHP7TIGgrBECMBcNgk21AFVlug6DQTIngLSrU4Wzt9MAxwrAlEwtadnG8Wv6WxkD6GFHF7BMZpEbVu9kQJL0yF08QFmCzGilDEnrhMHZ1er4Pw8PjzyuVhMtW7ZEr9cTHx9Px44dbV8bEBwcTGhoKNeuXWPo0KEF7tO8eXO+++47kpOTC7QCKpVK9Pqi40flcjmDBw/m//7v/5g9ezbVq1fP87pKpcLV1ZULFy6QlJTEp59+SlhYGADHjh2z+ryio6O5des2OBst7QcOHkQul5uTPQrCkrlNFsOizrdRo0bodDoOHz5sdgEnJSVx8eJFi62IAoGJAzcPMHLjSC4lGX88jWj+Iovdw3Dd8zkyJCINNVgZOp0ZIwdYVV1BIHA0Igs4F+WlFuDFuHRSMrW4KxU0r+5r/tBId6AANFn/qvq44qa0LgGmLPoB2y8L2PYyMIVRv359hg4dyrBhw1i/fj1RUVEcOXKEOXPmsGXLFqvHmzlzJnPmzOHrr7/m0qVLnDlzhlWrVjF//nwAXnjhBUJCQhgwYAD79+/n2rVr/P777xw8eBCA8PBwoqKiiIiIIDExEbW64Ps0e/ZsqlWrRrt27fjhhx84f/48ly9fZuXKlbRs2RKVSkWNGjVQKpV88803XLt2jU2bNtlUX8/V1ZXRr7zMxfNnOHH4AJMmvsVzzz1XZJyiJXPXrFkTmUzG5s2bSUhIMFtQc1OvXj369+/P6NGj+e+//zh16hQvvvgi1apVo3///lafi6BykqXN4u3tb/PYyse4lHSJUK9QdvZfzaqURNwOLkKGxBpdN1Y2/JaPX3laiD9BuUMIwFzUDza656KTM8l0cNHlojC5fx8O98dZIcfTxSjIHGkBNJeAsTIDGO65gJMzNaXSrQRy9QIuo0LQxbFq1SqGDRvG22+/TYMGDRgwYABHjx6lRo0aVo/1yiuv8N1337Fq1SqaNWtG586dWb16NbVq1QKMVq8dO3YQFBRE3759adasGZ9++qnZRfzMM8/Qu3dvunbtSmBgID/99FOB8/j7+7Njxw6GDh3K7NmzadmyJR07duSnn37i888/x8fHh8DAQFavXs26deto3Lgxn376KfPmzbP6nOrWrcuTT/Vn3LDBjB36DI2bNMtX2uZ+LJm7WrVqzJw5k/fff5/g4GDGjx9f4FirVq2idevWPPnkk7Rr1w5Jkti6dWs+t69AUBD7o/fTYmkL5h+aj4TEiIdGcKHnN3TbPgOiD5AuuTFe8wbX2s7ms+fbiD6+gnKJTKpkQS23bt0iLCyMqKgowsPD873+8Oy/SVSp2TiuAy3CfEt9fQCjfzjGzvNxTO7dkNe61GHutgss3nOVEe3DmfFUE4fM+cWOi3zzzxVeeLQGc55uZtWxOr2Beh/+hSTB0Q+6E+hlWYxLeno6ly5dolGjRri7Wx5/J0kSZ2/fRQIaVfXGWWH7h2tcWjZxadlU8VBSzc+6GMAHDYPBQFpaGt7e3shLWmHbAhJVau6kZgHGLPwgb1eHz1lRKO17ISiczMxMIiMjqV+/PgpXBR/s+oCvDn+FhESoVyjf9l1M3+hjcOBrAM4YwhmvncCQ3l0Y06l2hc70TU5OZvHuK3h4+xa5X0ZaKq93revwguvXr1+nVq1a3Lx5M1+YisB6xCfLfZR1RxC9QeJwrvg/wOw6cGQWcJSNGcAATgo5fu6l1w7OIIHpV4u9LIClZLgU5CK3tVgrboCgnHMi5gQtlrZgweEFSEi8/NDLnB+6g77/LTSLv9W6njyn+4gJz/bi1c51KrT4Ezz4iKCE+6gX5MX+K0lcLiMBGBmTRlq2Dk8XJ5qGGgPkPXMEoENdwEm2u4ABAjyVJGdoSkkAGsWCDChhCCAycyu4Ei5KYDW5BaBOb3sxb4HAkRgkAyq9ihGbRnA94zrVvavzbb9v6a0zwKq+kJ1KhsyDt9Wj2aNoy5JhrenaMKisly0QFIuwAN6HqSPIxbiyyQQ2Zf8+Eu6HU45r09EWQEmSuJ5o7L5Ry8oSMCbMtQBLoR+wSTjI5bIS/8I2CUgJoQBLmzwWQL24/oLyR7o6nWsp18jSZyEhMarlKM6OOUHvK3vh5xcgO5UL8nr0yv6YQ64dWDu6rRB/ggpDmQvARYsWER4ejqurK23atOHIkSNF7r9gwQIaNGiAm5sbYWFhTJw4kezsbLutp6x7Apvr/9W5VzDY0UkgiSoNKrUOmQzC/G2LgyvNTGCTBVBhB/eKSUAKD2TpIyyAgvKK3qAn+m40F5MuojFokMvkLH1iKd91/BCfNc/BIWPC0lr5k/TL/B8G7xr8NrYdrWr4lfHKBfezb98++vXrR2hoKDKZjA0bNuR5fcSIEeY+6aZH79698+yTnJzM0KFD8fb2xtfXl1GjRuWrMHD69Gk6duyIq6srYWFhzJ07N99a1q1bR8OGDXF1daVZs2ZWtc90BGUqAH/55RcmTZrE9OnTOXHiBC1atKBXr16FVttfu3Yt77//PtOnTycyMpIVK1bwyy+/MHXqVLutyZQJHJuWzd1Mrd3GtQSd3sCRnKLP7WrfqxTvYXYBO6YXsMn9G+rjhquzbT2QTf2AE6wQgLaWYMltASwpZgug8AGXOnopbwyguAeC8kC6Op3zCeeJzzB+D/m6+uLn7EdHrRZpaUe4cwKVzJNXNG8zNXMItYJ9+f319tQVPX3LJRkZGbRo0YJFixYVuk/v3r2JiYkxP+6vlDB06FDOnTvHzp072bx5M/v27WPMmDHm19PS0ujZsyc1a9bk+PHjfP7558yYMYPly5eb9zlw4AAvvPACo0aN4uTJkwwYMIABAwZw9uxZ+5+0hZRpDOD8+fMZPXo0I0eOBGDp0qVs2bKFlStX8v777+fb/8CBA3To0IEhQ4YAxvpmL7zwAocPH7bbmrxcnanm68bt1CwuxafzSLhjs5pyc+5OGulqHd6uTjQOvdeKztPBLuB7CSC2uX8hlwXQimLQTk5OGAwGMjMz83V9KAqDnUrAgEgCKUtyWwAlydgNxEkhguYFZYPeoOd2+m2z8FMqlNT0qYmUbSBTexPl9nHINGkcN9TjDc0bJCgCeeHR6rzfuxE+7qJ8UHmlT58+9OnTp8h9XFxcCq1BGhkZybZt2zh69CgPP/wwAN988w19+/Zl3rx5hIaGsmbNGjQaDStXrkSpVNKkSRMiIiKYP3++WSh+9dVX9O7dm3fffReAWbNmsXPnThYuXMjSpUvteMaWU2YCUKPRcPz4caZMmWLeJpfL6d69u7mA7f20b9+e//u//+PIkSM8+uijXLt2ja1bt/LSSy8VOo9arc5T+DY93eja1Wq1aLUFW/jqBnlwOzWL87dTeaha6f2q+++y8YPnkXA/DHodhhyDX44HmAy1rtA1l4Rr8cZrUsPf1ebx/dyMb6XE9GyLxzAYDKSnp5OQkAAYe69aEtOXlaVD0mlAriczs2RGbK3GOJaOko9V0ZEkCY1GQ1ZWVqlkL2rVaiTDPddvekYmLqJeGlD696Kyk6nN5Hb6bbQG42eXn6sfwR7BoNZy58YlfGL+w0mTxlJdPxbJBjOofS1GdqhJSE7pIkd8LpcHtFotkqTHYCja+yRJ+iK/U+25HjB+j6elpZm3u7i44OJie4u9PXv2EBQUhJ+fH48//jizZ882920/ePAgvr6+ZvEH0L17d+RyOYcPH2bgwIEcPHiQTp065eld3qtXLz777DNSUlLw8/Pj4MGDTJo0Kc+8vXr1yueSLk3KTAAmJiai1+sJDg7Osz04OJgLFy4UeMyQIUNITEzkscceQ5IkdDodY8eOLdIFPGfOHGbOnJlv+759+zh//nyBxzip5ICcv4+cwzfxjOUnVUI2Rxrn9c6OzRMbkKIGcCI9W+OQmIFDF43zZsbdYOvW6zaNcT1FBii4eifBpjVmZGRYXO8sWw+ZOhlKucTdGKunyoPWAOlaGQoZZMQJM2BpkqKWIWHM5paArAQJZ6H/BKWIhESGPoMsvbEepVwmx0vhRYo8lWRdHO76dJyyk3C78Ctjde9ASAveDzHgKV3lxH9Xy3j1jic9PZ2rt+W4ehRtCMnOSGdn9lW8vBxrMElMTATI17Jx+vTpzJgxw6Yxe/fuzdNPP02tWrW4evUqU6dOpU+fPhw8eBCFQkFsbCxBQXkTe5ycnPD39yc2NhaA2NhYc2F+EyZtExsbi5+fH7GxsQXqHdMYZUGFKgOzZ88ePvnkExYvXkybNm24cuUKb775JrNmzeJ///tfgcdMmTIlj+q+ffs2jRs3plOnTgUWggbQRNxh1+9nUbtVoW/fRxxxKvnQ6g1MOb4b0DOy72M0qnrvDyktS8uME7vRSzK69extdyvJkqiDQDp9Oj7M4w0CbRqj+q27LL9wGK3Clb59O1t0jFarZefOnbRt2xa5XI5Op7MoDmztkVv8cOgGfZoG8+bj+XvxWsO5O2nM+O0MVX1cWTW8dYnGqujodDoOHDhA+/btcXJy7EeDVi8xYdEBwBh3eylOxcTu9eglMiiB0r0XlZXDtw4zfd90bqffBuC5xs/xass32XcuEf+IRfTiABj0nMvyZ43/28wa+zR+nm5lvOrSJTk5mah/r+Hu5VvkfpnpqfToWLtUCkEDnD9/nmrVqpm3l8T69/zzz5v/36xZM5o3b06dOnXYs2cP3bp1s3ncikCZfbIEBASgUCiIi4vLsz0uLq5QX/z//vc/XnrpJV555RXAeLMyMjIYM2YMH3zwQYEWpPtNwyazsbOzc6FtnxqF+gJwOV6Fk5NTqbhgTt9JIVOjx8/dmabV/fIkOPjI7yVmaAwyPO3YrkqSJKKTjSVg6gZ729wKK8TPGMOXnKGx+poVdS8KIkkNt9P1yJxcSvyL08PDwO10PQa53uG/Xss7Wq0WnU6Hp6enw1uiJaSruZ1udCu1refF7St3ic0wVPp7YKI070VlI12dzrs732XZ8WUA1PSpyaddvuV6TBhvLdvBXMN8GsmjMSDjXO1XqP/0DFrv2oWfp1uluxfOzs7IZArk8qKTA2UyhdWf47auB8DLywtvb+9i9raN2rVrExAQwJUrV+jWrRshISH5ElN1Oh3JyclmrRISElKgljG9VtQ+RfU/dzRl5nBRKpW0bt2aXbt2mbcZDAZ27dpFu3btCjwmMzMzn8gz9Tu1ZwZh3SBP5DJIydRaldVaEkz1/9rUqpIvu9VJIcc1xzdm71Iw8elqMjV6FHIZYSVohVbFwxj7oNVLpGU5to9yerZxfE+Xkn/YmHp0qnWiDElpcjfLGMvj5epEVR9jHFVcWun8rQkqL39f+5umS5oaxZ8k55laM3jMay1TftEQ++/3/CxNppE8mmxlFQxDf6fZsHm4lsC6JKh43Lp1i6SkJKpWrQpAu3btSE1N5fjx4+Z9/vnnHwwGA23atDHvs2/fvjwxkDt37qRBgwb4+fmZ98mtd0z7FKZ3SoMyjbiZNGkS3377Ld9//z2RkZG89tprZGRkmLOChw0blidJpF+/fixZsoSff/6ZqKgodu7cyf/+9z/69etnFoL2wNVZYe6IcSm2dApCH7qWv/5fbhyVCWzKAK7u51aihuWuzgq8XI1rdLRoNl0DT9eSG7BN7nSNEIClikkA+rg5E+xt/IKNS7NfPU+BIDdp6jTG/DmGHj/24FZqGuGKV2nl9CfHzj/MscuxfKZYxgLlYjxkaqTwjri+cQCneg+2+6+yoFKpiIiIICIiAoCoqCgiIiKIjo5GpVLx7rvvcujQIa5fv86uXbvo378/devWpVevXgA0atSI3r17M3r0aI4cOcL+/fsZP348zz//PKGhoYAxP0GpVDJq1CjOnTvHL7/8wldffZUn/OzNN99k27ZtfPHFF1y4cIEZM2Zw7Ngxxo8fX+rXxESZBpcMHjyYhIQEpk2bRmxsLA899BDbtm0zB0pGR0fnsfh9+OGHyGQyPvzwQ27fvk1gYCD9+vXj448/tvva6gd7cS0xg4tx6TxWL6D4A0qARmfg2PUUANrWLlgAerg4kajS2N0CeD2xZC3gchPg6UJ6to5ElZq6QZ4lHq8wVNk51iOXkr9971kAHVNjUVAwabkEYFBOJmV8urAACuzPjqs7eGXjK8Sn+hKgn4ynoQNStpwkJFq7xbLU9RsCs6IAGXR5H1mnd6EYl6eg4nDs2DG6du1qfm4SZcOHD2fJkiWcPn2a77//ntTUVEJDQ+nZsyezZs3KEzq2Zs0axo8fT7du3ZDL5TzzzDN8/fXX5td9fHzYsWMH48aNo3Xr1gQEBDBt2rQ8tQLbt2/P2rVr+fDDD5k6dSr16tVjw4YNNG3atBSuQsGUeXTx+PHjC1XAe/bsyfPcycmJ6dOnM336dIevq36IF9vOxZZKR5BTt1LJ0uqp4qE0F6K+Hw+lgyyASSWvAWgiwFNJVGKGw7uBmK6Blx0tgFq9hMEg2aW4tKB4TBZAX3dngryMH7TxwgIosCN3s+8yYev7/HHyDl66qYRIYYAx47x1DV+mhp6g1dmPkWVlgWcwPPMd1OpUtosW2J0uXboUGSK2ffv2Ysfw9/dn7dq1Re7TvHlz/v333yL3GTRoEIMGDSp2vtKizAVgeaVBsKknsOMFoKn9W9vaVQpNnvB0UDeQexZA2+P/TJRWP2BzDKAdBGBut7dGb8BV/PIvFfK6gO9ZAIUIF9iDrZf/YuxP2yCzO/4Y31/uSgUDW1bjxVYBNDo+AyJ+Nu5cuys8vRw8RQa6oHIhBGAhmCxxl+PSHf6lZBaAhcT/AXg4qB/w9URjBnC4XSyApdMP2BwDaAcXsIvTPcGn1hpsboUnsI7cAjAwxwKoM0gkZ2rM7yOBwFpSs1OZtO1tNhyV460fAECYv5wxnRozsGU1PFMuwLp+kHQZZHLo+gE8NgksrEEqEDxICAFYCOEBHjgrZGRo9NxOzSLMv+QWsoLI1uo5Hm2M/2tXSPwf3OsHbE8XsMEgmfsA28MFbOoHXJFcwM4KGTIZSBKo9XqgcpV5KCtMAtDbzRlnhZwATyWJKg3xaWohAAU2sfXyVsb8OYb05Db46V8GYPbAhgx9tDYygOOrYdv7oMsGr1B4dgXUbF+WSxYIyhTxs6cQnBVy6gTmWAHjHecGPhmdikZnINDLhTqBhYuwey5g+wnA2LRs1DoDTnIZ1XxLXuDU9MWdYEU/YGuRJMmuZWBkMhlKRU4iiFZkApcWuS2AAEFeOaVg0kUcoMA6UrNTGblxJE+sfYLUlPr46Yzi74O+jXixTR1k6nT4fRRsfsso/ur2gLH/CfEnqPQIAVgE9U1xgA4sBXPQVP6liPg/yGUB1NhPAJri/2r4u+OkKPlbwRwDmOE4C2C21oDeYAzotUcMIOQqBaMXArC0SM28TwB6i0QQgfVsubSFJoubsDpiNW76VgTqJgLwymO1GN2pNsScguWd4ezvIFNAj49gyK/gUbi3RSCoLAgXcBE0CPGCU3DJgYkgh64WXf/PhIcDLICmDGB7xP8BBHo53gWcrjYKB5kM3O0Ur6d0UgA6YQEsRdLuswAGe4li0ALLSclK4a3tb/HDqR8AqOv1OPLkSagl6P9QKFP7NIQj38L2qaDXgE8YPLsSwh4t45ULBOUHIQCL4J4F0DECMEuj5+TN4uP/ADzNSSD2ywKOSrBfDUCAKh45SSAOdAGrTO5fpZPdEnOEBbD0ud8FLIpBCyzlz4t/8urmV4lRxSBDxpgWH3LkzGMk67Q8VjeAz58MR/77CDi/0XhAg77QfxG4O7ZPrUBQ0RACsAhMpWCuJKjQ6Q12cZPm5kR0Clq9RFUfV2oWU4bFEUkg9xJA7JPgEpCTzZml1ZOh1pnXbE/smQBiwiQA1VpRDLq0yBcDKIpBC4ohOSuZt7a9xY+nfwSgQZUGfNl9BZ9sUpOckUXTat4s7yZD+V1nSL0Bcmejy7fta0aXgUAgyIMQgEVQ3c8NN2cFWVo9N5IzzUkh9sKS+n8mHJEEYmoDZy8XsIdSgauznGytgSSVxjEC0I41AE0ohQWw1MmfBCJiAAWFs+niJl7d/CqxqljkMjlvt3ub99r9j+ErI7iZnEUNPzd+bnYS9x8/AoMWfGvAoNVQrXVZL73SYTAYSE1NtWhfX1/fPN2+BKWLEIBFIJfLqB/syalbd7kUm25/AZgrAaQ4TJ1A7CUA9QaJm8lZgP1cwDKZjABPF26lZJGgUlPDDsWl7yfdjjUATbjkxBKKGMDSQaMzkJVjbb3nAhYxgIL8JGUm8ea2N1lzZg0ADQMasrr/alqGPMLLq49y7k4atdzVbAlZjfueHcaDGvWDpxaCm2/ZLbwSk5qayvzNJ3H18Cpyv+yMdCY92RJ/f+GaLyuEACyG+sFenLp1l4tx6fRpVtVu42aodZy6mQoUnwAC9ncB30nNQqM3oFTICbVDCRgTVXIEoKMSQe5ZAO1Xr8/FVAZG5zgBePb2Xc7fSWPQw9WLtfY+6JisfzIZeLnmFYAJKjV6g4RCdAOp9Gy4sIGxm8cSlxGHXCbnnXbvMLPrTJRyF976JYL/riTSTnmV792Xooy6DQol9PoEHnlFuHzLGFcPLzy8fct6GYJiEAKwGBqEGH/F2DsT+NiNFHQGiWq+bhYVmbZ3K7hbKUbrX3U/N7t+2QY6uBh0erZRPHjZ1QJocgE7Lgbw/fWnOXs7jZpV3GljgcX3QcYkAL1cnMzvvQBPJTKZ0TKdnKExdwcRVD4SMxOZ8NcEfjr7EwCNAxuzqv8qHq1mzOCdvfk8f566xVinrbyn+BW5Sgd+tYwu39CHym7hAkEFQwjAYnBUJvBBC8u/mLB3K7hsnVHsuLvYt/WZo/sB27MNnInSKARtcm0eu5EiBKAp/s/9nhXXSSGniocLiSo1cWnZQgBWUtZHrue1La8RnxGPXCZncofJTOs8DVcno4X4233X+P2/U6xwXsrjigiQgCZPQ7+vwNW7TNcuEFQ0hAAsBpMF8HpSJtlavd16xVoT/we5LIAaHZIkldiNqM1xdzrZOQDX0f2AzTGA9swCdnZ8EojJcnn6VqrD5qgo3F8D0ESwt1EAxqdnAz5lsDJBWZGQkcAbf73BL+d+AaBJYBNW9V/FI9UeMe+z4eRtdvz1B1tdFlJVlgwKF+jzGbQeIVy+AoENCAFYDEFeLni7OpGWreNaQgaNQ0v+KzM9W8vZ23cBayyAxltlkIxlVtyVJbt1upxuGko7l7ZxdD9gUwygPcvAONoCqNEZyM4Z+9TNuw6ZoyJxfwawiWBvV87dSROJIJWM387/xutbXichMwGFTGG2+rk43bMCbztzm6u/z+Qn5TqcZAakKvWQDVoNIU3LbuECQQVHCMBikMlkNAjx4uj1FC7FpdtFAB69nozeIFGzirvFCRjuSgUyGUiSUQSVVABqc6xdTgr7/nI2WwAdVAzaES5gFyejVddRFkCT9Q+M/Zfj0rLNSQ+VkdRM43ujIAsgQLwQgJWC+Ix4xm8dz7rz6wBoGtSU1f1X0zr0XumW9GwtX/yxn8fPf8jbTmcAkJo9h+zJL8HFvlUZBILKhijAYwHmOEA7JYKY4/+siAWTyWTmUjD2yATW6o0WQHsXtzYLQAf1A3aIBdDBhaDTs/PeL1P2d2XlbpbxetwvAINM7eDSRS3AB51fz/1Kk8VNWHd+HQqZgg87fsix0cfyiL8DVxKZ+sViXr8wnE6KM2jlLuieXIjs6eVC/AkEdkBYAC3AnAlsp0QQc/yfhe5fEx4uClRqnV0ygXU51i6lnS2A5n7ADurocK8OoB3LwDg5tgxMWi4LIMCpW6n0bBLikLkqAiYXsPf9AtBbFIN+0IlTxTFu6zh+j/wdgGZBzVg9YDWtqrYy75Ol0TP3r3N4H1nAAqf1KGQSWb71cBvyIwQ1KqulCwQPHEIAWoA9LYB3s7Scu5MGGDuAWIMxDlBtHwtgTgygvZNATP2A07J1qHV6s3vVXqQ7oBOIKQnEUQIwvwWwcscBFhoD6CWKQT+oSJLEL+d+YfzW8SRlJeEkd2LKY1P4sNOHKBVK834no1P4+OfdTEyfRwfncwBomw/B7cl5oLRPwXqBQGBECEALMAnAWylZJe5xeyQqGUmC2gEeVseB2bMdnCkL2NnJvgLQx80ZJ7kMnUEiSaWxa5FpAJXaKB7sWwYmpxOIoyyAuerepat1nLqVisEgIa+kxY6LSgIBiBMWwAeKOFUcr299nfWR6wFoEdyCVf1X0bJqS/M+Gp2Br3dd5vTeP1jivIhARRp6J3cU/b7EucXzZbX0Bw5r27QJHmyEALQAfw8lgV4uJKSruRyv4qEwX5vHMvf/tdL9C7nawWlKLgB1hhwBaGcRIpfLqOKpJC5N7RgB6IAYQHMZGAdbAB+q4cuRqGTSs3VcT8qgtp1bC1YUiioDA8YMctENpOIjSRI/n/2Z8X+NJzkrGSe5Ex92/JApHafksfpdiE3jnZ9P0CtxFaudNyKXSegDG6N47nsIrF+GZ/DgYW2bNsGDjRCAFtIg2IuEdDWXYtNLJgCtrP+XG5Pb075JIPb/kg3wdCEuTW33UjCSJDm2ELTOMUkgphhAfw8lTav5cPxGCqdupVZaAWiyAPq6KfNsr+LpglxmLHWUpFITVIkzpSs6sapYXtvyGhsubACMVr/VA1bzUMhD5n30Bonl+66xZudBvlB8QxunC8YXWo9E0XsOONv3x6PAiGjTJjAhsoAtxB5xgCkZGiJjbIv/Azu7gHOSQJztnAUMxi9yMPZ1tSdqncEsXCuSBTAtl9WyeXVjgePKHAdYmAtYIZeZs8hFHGDFRJIk1pxeQ+NFjdlwYQPOcmdmdpnJ0dFH84i/awkqnlt2kMM7fmaj0/u0kV/AoPSEZ1ZAvwVC/AkEpYCwAFpIgxCjtaYkPYEPRxmtf/WCPG1qdWVqB6eySxawUUg5QgAGOKgYdG7Lp0cJ6yDm5p4F0LF1AL1cnWmYk1F+qhJ3BClMAIIxDjA+3dgOrpnoBlKhiEmPYeyWsWy6uAmAliEtWT1gNc2Dm5v3uZqgYtHuK2yJiGai/FfGKv8EQAppjnzQaqhSpyyWLhBUSoQAtBB79AS2tv/v/Xg4wALo5IA4q0AH9QM2xf95ujjZNYHCxdmUBOIgF3BO3TtvV2daVPcF4NydNDQ6g7kGYWVBrdOTlVNvsWAB6MKZ2xDvoDJCAvsjSRL/d/r/mLBtAqnZqTjLnZnWeRqTO0zGWWG8xxdi01j4zxW2nImhqpTIGuVCHpZfMg7wyGhkPWeDs3D5CwSliRCAFlIvRwDGp6tJydDg56Es5oj8lCT+D8BTaU8BmGMBdIAAcVQ/YEfE/8G9OoCOSwIxWQCdqFnFHR83Z+5mabkYm06z6pXLymWy/slkBbvxA71EJnBF4k76HV7d/CqbL20GoFXVVqzuv5pmwc0AOHPrLt/8c5kd5+MA6C4/zlduy/EwpIOLD/T/Bhr3L7P1CwSVGSEALcTTxYnqfm7cSsniUlw6bawUcYkqNZfiVABWH2vCZAG0RxKIo7KAwXH9gE3JFPasAQi5OoE4uBC0t5szMpmM5tV9+PdyIqdupVY6AZi7JE5BVlxzOzjRDaRcI0kSP5z6gbe2v2W2+k3vPJ33OryHs8KZ4zdSWPjPZXZfTABAKdOxJHgT3VJ/AwMQ2gqeXQn+tcr2RASCSowQgFbQINjLZgF4KMf61zDEC38brIdQcZJAHNUPOLcL2J443gKYt3TNQ2G+RgF4M5UX29Z0yJzlFXP8n3vBnVzu1QIULuDyyu2024zZPIatl7cC8HDow6zqv4omgU04dC2Zhbsvs/+K8fNOLoORjeW8mz4f1/gI4wBtX4fuM8HJts9BgUBgH4QAtIJ6wV7suhBvUyawSQDakv1r4l4MYMlj1RzVCxjuCcAkO/cDNlk+7ZkBDI5vBWcSgN6uRtFjigOsjIkgRSWAgLAAlmckSWJ1xGombp/IXfVdlAolHz72EUOavMa1hCxmrj/I0espgDG2+OlW1Xgn7BJB/7wN6rvg6gMDlkDDJ8r4TAQCAQgBaBXmTOBYldXHljQBBHJnAdvTAuiAOoA5/YCTMzR2LejruBhA43V1XBmYHBdwjnBtHmZ0+16OV6FS6+x+PuWZ4gRgkGgHV+ZIksTt1CwS0tUkpKtJVGm4mhjP7+f+5nZqGq58QBV5CM66KqzYJrFi27/mY5UKOc89Up2xHapT/egn8Ndy4wvVHzG6fH1rlNFZCQSC+6k83zx2IHctQEmSkMksEzbxadlcTchAJoO2tWwXgGYXsD06gTiwDIy/uxJZTkHf5AyNTSVvCuJ+V6q9uBcDaP8sYEmScq3bKHqCvFwJ9XHlzt1szt6+WyKrcEXjbmYxAjBXNxCd3uAQC7WgcDI1Ol5efZRD15ILeLUZpm68egPoMX6GuDrLCfJypXujYF7tXJtg7W34rT/EnDLu3OFNePx/oCj4ngsEgrJBCEArqBPoiVxmtGLEp6st7uVryv5tXNW70NgnS3BIGRgHWACdFHL83JUkZ2hIVKntJgDvWQDt+0XiSBdwpkaP3mD8ovR2u/fn1iLMlzt3Yzl1M7VyCcCckjg+bgXHf1XxcEEhl6E3SCSqNIT4iNIgpYVWb2DcmhMcupaMk1xGgJcTqZqbJKuvo5elEuLtzvCWA2lWtSYBXi4EeroQ4OWCh1Jx78fw2fWwaQJo0sHNHwYug/o9y/bEBAJBgQgBaAWuzgrCAzy4lpDBxdh0iwXgoRKWfzHhaccsYLMLWO4YC0uAp1EA2rMWoDkJxO4xgI5zAZusfwq5DLeceoMAzav78tfZ2EoXB1icC1ghlxHo6UJsWjbx6dlCAJYSkiQxdf0Zdl9MwNVZzvMd45l//A3SScfF3YVZXWcxqd0kFHJFwQNos2DbFDi+yvi8RjtjVw+faqV3EgKBwCqEf8VKGuS4ga3pCGKP+D+4ZwHM1hrQ6UsmVnQGUx1A+1sAwTG1AM1JIHaOmTO5gHUGyWytsxfpueL/cocMtAirnC3hihOAcC8RRMQBlh5f7LjEuuO3kMvAv+oGZh4cQbomnbbV2xIxNoJ3O7xbuPhLvAzfdc8RfzLo+DYM3yzEn0BQzhEC0Eqs7QgSczeL60mZyGXwSC3/Es1tSgIByNCULF7tXicQx7wFqjhAAKY7qA6gS65i2Pa2AqblagOXm2bVfJDJMAfbVxYsEYCiGHTp8sPB6yzcfQWAdNflHExYjquTK/N6zOO/kf/RMKBh4Qef/hWWdYa4s+AeAC/+Dt2mgUI4lwSC8o4QgFbSIMQ6C6DJ+tesmo+5DIituDgpzFm7JY0D1DowCQTu9QNOsKsAdEwWcO52bPZOBEkrJHHFy9WZOoHGrPLTlcgNnGaFBTBeCECHs/VMDNM3ngMg1en/SGQT7cPaE/FqBG+3f7twq58mEzaOh/WjQZsB4R3htf1Qt1sprl4gEJQEIQCtxGQBvByvwmCBu9AkANuW0P1rwl6JIDoHloGBXLUA7RkDqHZMDKCTXIapUo3dLYBZJhdwfsFzrx5g5XEDp2YZ3w9FC0BRCqY0OHg1kTd+Oo4EpCu2onbdwPye89k3Yh8NAhoUfmD8Bfj2cTj5IyCDzu/DsI3gFVJaSxcIBHZACEArCa/ijlIhJ1Oj53ZqVrH7H7RDAejceCjtkwiicWAhaIBAB8YAettZAMpkMoe1gyuqdM1D5jjAVLvOWZ6xJgbQ3sWgs7V6PvrzPEeiCipxUrn459IFhq7Yi94gI1N+kIa1T3P6tdNMbDexcKsfwMk1sLwLJESCZ7BR+HWdAkUdIxAIyiVCAFqJk0JOnSCj6664OMCbyZncSslCIZfxSHjJ4v9MeNqpG4ijLYCO6Ad8rxWc/euJmTKB7e8CvtcH+H6a5+oIIkn2TT4pr1giAB1VDHrrmRhW7o/ivd9OVZrrfT8GycBne5czfNVRDAZXNIpIJj8RxL6Re6hXpV7hB6pV8MdY2Pg66LKgdhcY+x/U7lxqaxcIbGHfvn3069eP0NBQZDIZGzZsML+m1WqZPHkyzZo1w8PDg9DQUIYNG8adO3fyjBEeHo5MJsvz+PTTT/Psc/r0aTp27IirqythYWHMnTs331rWrVtHw4YNcXV1pVmzZmzdutUh52wpQgDaQIPgHAFYTBygqfxL8+o+dotbs1c3EHMWsMNiAO3fDzjdQS5gcFwtwKIsgA2reqFUyEnN1HIzuXhrckVHrdOTrTVe3yIFoIMsgKa/1+tJmVywMInrQSIqJYquK5/k620GFJI/zsoEtozrx9sdJhRt9Ys7B992hVM/gUwOj38IL/4BnkGlt3iBwEYyMjJo0aIFixYtyvdaZmYmJ06c4H//+x8nTpxg/fr1XLx4kaeeeirfvh999BExMTHmxxtvvGF+LS0tjZ49e1KzZk2OHz/O559/zowZM1i+fLl5nwMHDvDCCy8watQoTp48yYABAxgwYABnz551zIlbgEjVsoH6FiaCHLRT/b/c2CsG0BTr5mSnNm33E+B1rx+wNV1TCkOt05vX7IjWaY5zARecBQxGq2OjUG9O3Uwl4lYqNaq423Xu8obJ+ieTFd3NxRQDmKjSoNUb7PYj5Wr8vRaOf52NpVFVb7uMW94xSAaWHF3C5J3/wzNjKq5SGJ5uOrZNGER1P4/CD5QkOPE9/DUZdNngVdVY2y+8Q+ktXiAoIX369KFPnz4Fvubj48POnTvzbFu4cCGPPvoo0dHR1Khxr3Whl5cXISEFx7muWbMGjUbDypUrUSqVNGnShIiICObPn8+YMWMA+Oqrr+jduzfvvvsuALNmzWLnzp0sXLiQpUuXFnkOWVlZSJKEu7vxO+LGjRv88ccfNG7cmJ49bS+0LgSgDZhqAe6+EM+wlUcK3e/kDWNj9JLW/8uNvdrB6QwmF7CDysB4GF3AWr1EWpauRB1Q4J77FxwjAE0WQPsngRQdt9iiug+nbqZy6mYqT7UItevc5Q1TQoyXixPyIn54+LsrcZLL0BkkElVqqvq42WX+K7kE4LazMUzqUd8u45ZnrqVcY9SmUeyJ2kegZiquhkZ4ushZP/bxosVfdhpsfgvO/m58XrcHDFwKHgGlsm6BoCjS09NJS0szP3dxccHFxT4dp+7evYtMJsPX1zfP9k8//ZRZs2ZRo0YNhgwZwsSJE3FyMn6uHzx4kE6dOqFU3utw1KtXLz777DNSUlLw8/Pj4MGDTJo0Kc+YvXr1yuOSLoz+/fvz9NNPM3bsWFJTU2nTpg3Ozs4kJiYyf/58XnvtNZvOVQhAG2hWzQcnuYy0bB37LiUUua+XixOta/rZbW4PO3UDcWQvYDB2TfFycSJdrSNBpS65AMw5X3elAoUDrJZKcwygYyyAhZUAMmYC36gUiSAmC6Cve8Ft4EzI5TKCvFy4czebuDT7CMBsrZ7o5Ezj+DK4FKfiSryKujnxvA8aBsnAoiOLeH/X+2RqMgnSv4WboS0uTnJWjWxjrmZQIDGnYN0ISL4GMoWxrl/7CeCgmqECgbU0btw4z/Pp06czY8aMEo+bnZ3N5MmTeeGFF/D2vuchmDBhAq1atcLf358DBw4wZcoUYmJimD9/PgCxsbHUqlUrz1jBwcHm1/z8/IiNjTVvy71PbGxsses6ceIEX375JQC//fYbwcHBnDx5kt9//51p06YJAViaBHm7sv719nksCoXRrJoP7kr7XWZPe7mAHZwEAkY3cLpaR6JKXeIvWkfVADThMAtgzrpz9wHOTYswXwDO3rmLTm9wWFZ2ecCSBBATgd6uOQLQPnGAUYkZGCSjJbZlDT/2Xkpg29kYxj9eROJDBeVK8hVGbRrFvhv7AGjhOZXUxPbIZfD1Cy0LT0iTJDj6HWyfCnoNeFeHZ1dCjTaluHqBoHjOnz9PtWr3Os3Yw/qn1Wp57rnnkCSJJUuW5Hktt+WuefPmKJVKXn31VebMmWM3y2NRZGZm4uVl/NG2Y8cOnn76aeRyOW3btuXGjRs2jysEoI00r+5rzuIsTUxJICXPAnasBRCMxaCjEjPsUgvQUTUATdyLAbRvFnBRMYAAtQM8zJbSS3EqGoc+uHFp1gjAYC/7FoM2/VirG+RJn6Yh7L2UwF9nYx8oAWiQDHxz+Bum7JpCli4LD2cPXqq3mL+OG0NQPurflF5NCqnVl30XNr0B5zcan9fvAwMWg7t9qhcIBPbEy8srj4WupJjE340bN/jnn3+KHbtNmzbodDquX79OgwYNCAkJIS4uLs8+puemuMHC9iksrjA3devWZcOGDQwcOJDt27czceJEAOLj40t0HR5cc8MDir1cwOZWcI60ANqxFqDKnE1r/xIwkCsLWOuYLODCXMByuYxm1XPqAT7gHUHuZlohAHMSQeLt1CYvtwDs2SQEhVzGuTtpRCdl2mX8suZy0mU6r+7MW9vfIkuXxeO1Hmd1n4PsPGmM2RvftS4vtq1Z8MG3j8PSjkbxJ3eGXp/ACz8J8SeoFJjE3+XLl/n777+pUqX4mP2IiAjkcjlBQcZM+Hbt2rFv3z60Wq15n507d9KgQQP8/PzM++zatSvPODt37qRdu3bFzjdt2jTeeecdwsPDadOmjfmYHTt20LJlS4vP9X6EAKxg2MMFLEmSw8vAgH1rAZoEr5fDXMBGy6rJNW4vzIkPRVguTW7gB70l3F1TQoxFAtD448FeLuArCfcEoL+HkjY5fbn/Ohtjl/HLCr1Bz5cHv6TF0hb8F/0fnkpPlj6xlMU9/2DmhjvoDBL9Hwrl7Z4FJLxIEhxaAit6QeoN8K0BL2+HduOMqdoCwQOASqUiIiKCiIgIAKKiooiIiCA6OhqtVsuzzz7LsWPHWLNmDXq9ntjYWGJjY9FojJ6rgwcPsmDBAk6dOsW1a9dYs2YNEydO5MUXXzSLuyFDhqBUKhk1ahTnzp3jl19+4auvvsrjOn7zzTfZtm0bX3zxBRcuXGDGjBkcO3aM8ePHF3sOzz77LNHR0Rw7doxt27aZt3fr1s0cG2gLwgVcwbBHJxBdrhZ2zg4M7LanBdBcA9DBMYBqrf1cwDq9gQyNcbwiBWBOKEHEzQe7JZwlbeBM2LsY9NVcFkCAPk1DOHA1ib/OxvJq5zp2maO0uZR0iZEbR3Lg5gEAutfuznf9vsNNEczARQdIV+t4NNyfuc82z1+GKTPZ2Mv34hbj80b94KmF4OZbuichEDiYY8eO0bVrV/NzkygbPnw4M2bMYNOmTQA89NBDeY7bvXs3Xbp0wcXFhZ9//pkZM2agVqupVasWEydOzCPufHx82LFjB+PGjaN169YEBAQwbdo0cwkYgPbt27N27Vo+/PBDpk6dSr169diwYQNNmzYt9hz++ecf2rdvn89d/Oijj1p9PXIjBGAFwx4uYG0uK1fpuIDtEAOY7dgYQHMSiB0tgLnvUVGu6xY5LeEuxaWTpdHjpnww22pZEwMYZEcLoN4gcS0xA4B6QcZA6l5NQpi26RwRN1O5k5pFqK99Ss2UBnqDngWHFvDh7g/J1mXjpfTii55f8EqrV8jS6nl++SFup2ZRK8CDZS+1Nlu3zdw8Cr+NhLs3QaGEnh/Do6OF1U/wQNKlS5ciO/8U1xWoVatWHDp0qNh5mjdvzr///lvkPoMGDWLQoEHFjnU/Tz31FDqdjkceeYQuXbrQuXNnOnTogJtbyT63hAu4gmEPF7BWn8sC6NAkEDtaAHOSKRxlAVQ6IAbQFP/n6iw3j18QId6uBHm5oDdInLvz4FoB06xJArFjDODN5Ew0OgOuznKq5Qi9IG9XHs4pz7TtbPFlGMoLFxMv0nFVR97Z+Q7Zumx61unJ2dfPMrr1aAwSvPlzBKdv3cXfQ8mqEY/g55Gr5I7BAPu/hlW9jeLPrxaM2gFtxgjxJxCUY1JSUti1axd9+vThyJEjDBw4EF9fXzp06MCHH35o87hCAFYw7JEFrMtl5XJoGRhHxABWIAtgWjE1AE3IZDJzHGDEA1wP0Kos4BwBmJyhKXFpHlMCSO0AzzwFqPs0rQpUjDhAvUHPvAPzaLG0BQdvHcTbxZvv+n3HtqHbqOFj7Fbw8ZZIdp6PQ+kk59thrQkPyFXoOSMJfnoedv4PDDpo8jS8ug9CbQ8gFwgEpYOzszMdOnRg6tSpbN++nUOHDvHCCy9w5MgR5syZY/O4QgBWMEwCqGQuYKMF0EkuK3GLtqKwZz9glYPrADqiFZypC4glorWFORP4wbUAWiMA/dydzT9OEkr4AyJ3Akhuejc1xtMcu5Fi977D9iQyIZLHVj3GuzvfRa1X06tOL86+dpZRrUaZ/36/P3CdlfujAJj/XAta18yVwXvjICzrCJe3g8IFnvzSWN/P9cEtOSQQPEhcunSJ5cuXM2TIEKpVq0bnzp25e/cu8+bN48SJEzaPK2IAKxi5ewHb2mO3NErAwL1+wFlaPZkaXYkKYqerHV0GJqcTiB2TQIqrAZibypAJbI0AlMlkBHm5cjs1i7i0bLPr1hYuxxUsAEN93WgR5supm6lsPxfHS4WVSSkj9JKeeQfnMXPfTNR6Nd4u3izotYARD43I83e/KzKOmX+eA+C93g14snlOS0GDAfZ/Cf98DJIeqtSFQashpFkZnI1AILCVhg0bEhgYyJtvvsn7779Ps2bN7GK8ERbACoZJAOoMks3WKpMAdGQGMICHUoGrs3GOkloBK2ISyL0uIMULnubVfAG4kZRJSkbJLablkXut4CwT8aZEkJIWgy7MAgjQN8cK+NeZ8uUGPp9wnvcvv8/U3VNR69X0qduHc6+fY2TLkXk++M/evsv4tScxSPD8I2G8ZspoViXAmmdg10dG8dd8MIzZK8SfQFABmTBhAtWqVeOjjz5i7NixfPDBB+zYsYPMzJLVMRUCsILhkcuKZmsiiLkGYBGJCfZAJpNRxcP4JV5SN56j6wA6Jgmk+BqAJnzcnamVE7P1IBaEVuv0ZOdcW0sEMUCwV8kTQSRJylcCJjemOMDDUckklwPhrTPo+PS/T3l05aNczryMj4sPq/qvYsuQLVT3rp5n3zupWby8+ihZWj0d6wUwa0BToziM+heWPgZX/wEnN2N5l4HLwOXB7HssEDzoLFiwgBMnThAbG8uUKVPQaDR88MEHBAQE0KFDB5vHFQKwgqGQy3BzLlkiiNkFLHd85p/JDVzSRBBHt4Iz1wG0pwXQVPjYQre1OQ7wAawHaLL+yWSWi3h7FIOOS1OjUutQyGWEV/HI93qNKu40ruqN3iCx83zJsoGzNHpGrjrCa/93PE+pJUs5F3+OdivaMWXXFDR6DQ97P0zEmIh8Ll8w/rh4efVR4tPVNAj2YtHQVjjLJNjzGfzwFKhiIaABjNkNrV4SWb4CwQOAXq9Hq9WiVqvJzs5GrVZz8eJFm8cTArACUtJagNpS6ANsIjAnE7ik/YDTHZ4EYooBtL8F0NtC0fogxwGaSsB4uzrnycQtiiDvkheDNmUA1/R3L7QUT99mRjfw1jO2C0BJkvhww1l2XzT2GF60+4rFx+oMOj759xNaLW/FsTvH8HX1ZUW/FXxQ6wOqeVXLt79Wb+D1NSe4EJtOoJcLK0c+grc2GX4cAHs+AckAD71oFH9BjWw+J4FAUD6YMGECzZs3Jzg4mFdffZU7d+4wevRoTp48SUJCgs3jiiSQCoini4JEFWRobHQBm2IAHZwEAvarBejoOoCOiAFMz7audE3znI4gp26l2pzgU16xJgHERJBXyS2AV+LTgYLdvyZ6N63KvB2XOHA1kbtZWqvWaOLXYzf5/cQt8/Nv/rlClwZBPJQj6gvjTNwZRm4cyfGY4wA8Wf9Jlj25jEDXQLbe3Jpvf0mSmLbxLP9eTsTNWcHK4Y9QLekQrB8NGQng7G7M8m3xvNXnIBAIyicxMTGMGTOGLl26WNQ5xFKEAKyA2MsC6FQKFkB79APW6AzmhBdH1QFUOqAVnLkOoIWCokmoN05yGYkqDbdTs6ju5263tZQ1qZnWC0BTLcCEEsQAFpUAYqJukCf1gjy5HK9iV2QcT7eqXui+BXH+ThrTNhqzcN/t1YALsen8eeoOk36JYMuEjgV2dtHqtczdP5eZe2eiNWjxc/Xj6z5fM7TZUGQyWZ6m8rlZuvcaPx25iVwGCwc3o9mlb2DfPECCoCbGLN/AAvr+CgSCCsu6descMq5wAVdAPErYDaRUYwDtYAHMfZ4eju4FbMc6gNZaAF2dFTSsamxVdvoBqwdoiwUw2OwCLokFsHgBCNCnmTEZxFo3cFq2ltfXHEetM9C1QSCvda7DrP5NCPF25VpiBnP+isx3zOm407T5rg0f7v4QrUHLUw2e4tzr53ix+YtFWn3XHbvJZ9suAPBp9yp0Ozoa9n0OSNBqOIzeJcSfQPCA8uOPP9KhQwdCQ0O5ceMGYEwO2bhxo81jCgFYASlpOzidwShyimpPZi/s0Q/YZOl0c1Y4LG7RJSexpqRdJ3JjaSeQ3JjdwA9YR5CSuIBTMrWodbZZZi0WgDnlYPZdTrDYsi5JEu//fprrSZlU83Vj/nMPIZfL8HVX8vmg5gD8cPAGey8ZY3S0ei0f7f2Ih5c/zMnYk/i7+bPm6TVsGLyBql5Vi5xrx7lY3l9/BoBPm8fx3PEhcGM/KD3hmRXw1NfgXHH6GQsEAstZsmQJkyZNom/fvqSmpqLXGz8PfX19WbBggc3jCgFYAbnnArbtS1Gju9cJxNHYwwKY7uAagABKhckCaM9C0NYXr34oRwA+aC3hTALQUnc4GOsFmu5LvA2JIKmZGvMPjzqBRQvAhiFehFdxR6MzsPtCvEXjrz5wna1nYnFWyFg4pGWevrsd6wUyon04AO+uO8W/USd49LtHmb5nOlqDlgENB3Du9XMMaTak2FjPQ9eSGP/TSWQGLSurb+b5SxMhM8lY0+/VfdDsWYvWKxAIKibffPMN3377LR988AEKxb2QkocffpgzZ87YPK4QgBUQT3M/4JJZAEsjC9jcD7gEcVyOrgEI4OLsiCQQk+ixfN2mTOCzt++iz6nX+CBgiwVQJpPdKwZtw/vHZP0L9XEtNnRAJpOZ3cCW9AY+GZ3CJ1uN7t2pfRvRsoZfvn0m925IrQB34tPVPPPdOiJiIvB382ft02tZ/9x6QjxDip3n3J00Rn9/jCq6BLb5fMbjiWuNLzwyGkb9DVXqFDuGQCCo2ERFRdGyZf6+3S4uLmRkZNg8bpkLwEWLFhEeHo6rqytt2rThyJEjRe6fmprKuHHjqFq1Ki4uLtSvX5+tW/Nnyz3ImIpB2ywAS7EMjMkCmJats9m6plLnZACXhgXQjmVg7vUCtlz01A3yxF2pIEOj52pOAsODgC0CEO7FAdrSDcQkAOsU4/41YXID776QQJam8PdqSoaGcWtOoNVLPNGsqtnSdz8Xk8+Q4DwPCR3u+sfoEvIO518/zwvNXrAowzs+C0b9cIJHtYfZ4TaVuupz4OINg76HJ+aBs6tF5yUQCCo2tWrVIiIiIt/2bdu20aiR7aWeyjQL+JdffmHSpEksXbqUNm3asGDBAnr16sXFixcJCgrKt79Go6FHjx4EBQXx22+/Ua1aNW7cuIGvr2/pL74MKWkWsKaUegGD8QvfSS5DZ5BIztBQ1cf6OCVH1wAEzC3r7GUBzNbqzWNZk7mskMtoWs2HI1HJRNxMpX6wl13WU9akWdkGzkRJikFbGv9nolk1H6r5unE7NYu9lxLo3TS/hc5gkJj4awR37mZTK8CDT5/J35NTo9fw8b6P+eS/T9AZdIS4BeOS9QyJsd3R67wtWktcWjbfRkqM1a9ktHIrSEBoS3h2FfjXsmgMgUDwYDBp0iTGjRtHdnY2kiRx5MgRfvrpJ+bMmcN3331n87hlagGcP38+o0ePZuTIkTRu3JilS5fi7u7OypUrC9x/5cqVJCcns2HDBjp06EB4eDidO3emRYsWpbzysqXESSClaAGUy2X3SsHY2A+4NASgUmHfQtCmBBCZDDyV1q3bVDvuQUoEsdUCGJTTDi7OFhewBSVgciOTycxWwMLcwEv2XmXPxQRcnOQsHtoqn3X3RMwJHl7+MB/t+widQcezjZ/l+KQ5PBTmS3q2jnfWncJQjGs/NVPD1FVbWS59xGinHO9G29fh5e1C/AkElZBXXnmFzz77jA8//JDMzEyGDBnCkiVL+Oqrr3j+edtrfpaZBVCj0XD8+HGmTJli3iaXy+nevTsHDx4s8JhNmzbRrl07xo0bx8aNGwkMDGTIkCFMnjw5T2BkbtRqNWr1vS+P9HRjYVitVltora3yjquT0eKQnm3bOahzjlHIKJVr4O+uJC5NTezdDBoG36ttZ5q7uDXczTTePw+l3GHrlWN0+al1ervMkZJutFh5ujih1+vQW+H9blrVKFhO3Uwt1feopffDFlIzjeLfw7nwGncFEeBhFFixqZlWr+tKnPFvPdzf1eJjezQK5Lv/ovg7Mg5VltpcHgjg0LVkvthhbLs0/clG1A1wM4+r1qn5ZP8nzD0wF72kJ8AtgK97f82zjYwJGnOfbkL/xQc5cDWJFf9dZUS7mgXOn6nRsXTZNyxM/xJveSZ6pTfSUwuRGvQ1WgEr6GdWRcaRfxeljVarRZL0GAxFfyBJ0r3PQWv2Nz2sPcaa9VdWhg4dytChQ8nMzESlUhXoJbWWMhOAiYmJ6PV6goOD82wPDg7mwoULBR5z7do1/vnnH4YOHcrWrVu5cuUKr7/+OlqtlunTpxd4zJw5c5g5c2a+7fv27eP8+fMlP5Ey4HKiDFAQfSfOpvjHU3eMx8fHxrB16227r+9+pCw5IOefA8fIvJLf+rFz584ijz8VbTw+MfY2W7fedMgaM7QAThgk+HPLVkrqHb+RbhzPWdJafY9iM43HXom7WybxrcXdD1uIT1EAMs4cP0yqFa0rYxKM79XzUdbde40ebqca57x+6hCJFv6pGyTwcVZwV63nq1+209TP+H69q4HPTyswSDIeDTTgEXeKrVtPAXAl8wpfR39NdHY0AO192/Nq9Vdxj3Jna9S9+/dkdRnrohR89tcFDLfPEXJfnW+DTov8/C+8r98BMoh1rcPpOuPIugpcrVxxzuURR/xdlDbp6elcvS3H1aPo0JLsjHR2Zl8FsGp/Ly8vq+fw8rI8zCUxMdHifR9U3N3dcXe3T5OACtUJxGAwEBQUxPLly1EoFLRu3Zrbt2/z+eefFyoAp0yZwqRJk8zPb9++TePGjenUqRPh4eGltHL74noxgR8un8TVy5e+fdtaffytf6PgxmVq1qhO3772aytTGHuyznAhIoZqtRvSt9M9F5ZWq2Xnzp306NEDZ+fCXYPHtlyA29E0bVCHvt3rOWSNmRodU4/9A8Dj3XuWuOD0v1cS4ewJgny96Nu3vVXHZqh1zDn1D9l6GR0f72FVEklJsPR+2MLkY38DBvr26EKYFR1OfK4msebKcQwuXvTt28Hi487dSUM6cgg/d2ee69/TqrWekCL58fBNktzC6Nu3KTq9geGrj5OuTaFBsCffjWmDm1KBWqdm9n+zmXdqHnpJT6B7IF/3+ppnGj1T4Lh9JIm4H0+w73ISG+P9WDemjbkWpyHpGnGrXqSG/hIAtxu+zHHXx+jes4/d74XAOhz5d1HaJCcnE/XvNdy9fIvcLzM9lR4dawNYtb+/v7/Vc/j7+1u8/uvXr1u8b0WnVatW7Nq1Cz8/P1q2bFlk4tiJEydsmqPMBGBAQAAKhYK4uLg82+Pi4ggJKbg8QtWqVXF2ds7j7m3UqBGxsbFoNBqUSmW+Y1xcXHBxcTE/T0tLA8DZ2bnC/jH7uBvPJ0Ojt+kcDJLxjeTipCiVaxDkbUz8SMnSFThfcfciU2OMy/Nxd3HYej3k995Tkqzk1yUn5A1vN6XVY/k6O+Pj5szdLC0JGXr8vUq3JZy9/zaytXqyc2Irq3i5WzV2qJ8HAPHpGquOu55sdMHXC/Ky+lz6Nq/Gj4dvsutCAsgVfLPrKkeup+ChVLD4xdZ4e7hy9PZRRmwcwfkEo2nx+abP802fbwhwDyhy7HmDHqLngn2cj0lnyb7rvNOrAdLZ9ajXj6OGIZNkyZNbnefTqOPTSFu3VujPqQeNB+FeODs7I5MpkMsLDpkyIcv1GWjN/qaHtcdYs/7KQv/+/c3apX///g7pDV9mAlCpVNK6dWt27drFgAEDAKOFb9euXYwfP77AYzp06MDatWsxGAzI5cZfzpcuXaJq1aoFir8HlZImgWgNpZcEAiXvB2wuA+PAJBAnhRyFXIbeINmlHVyaDTUAc1PVx5W7WVru3M2iQUjFzgQ2ZQDLZNbXcgzOSQK5m6UlW6vH1bnoLxUT1paAyc2jtfyp4qEkKUPDnK0XWLk/CoDPnm1ONT8npvw9hbkH5mKQDAR5BLHkiSU83ehpi8YO8nblk4HNeH3NCb7bc57hyV8ReHENrsBRQwOS+yyhV7vWlTrWSSAQkMerOWPGDIfMUaZZwJMmTeLbb7/l+++/JzIyktdee42MjAxGjhwJwLBhw/Ikibz22mskJyfz5ptvcunSJbZs2cInn3zCuHHjyuoUyoR7vYBtq6unK8UyMFDybiDmQtAOrAMI9/oB26MdnKkItK3u21Bfo9U0JtX2PrjlBXMXEFdn5FZ2n/F2czLflwQrMoGtLQGTG4VcRs8mRi+ESfwNb1eTQP+btFrWik/3f4pBMjCk2RDOvX7OYvFnom+zqrza2MB65+kEXlwDwCLdU0T2XEuvdq2tXq9AIHiweeWVV9izZ4/dxy3TGMDBgweTkJDAtGnTiI2N5aGHHmLbtm3mxJDo6GizpQ8gLCyM7du3M3HiRJo3b061atV48803mTx5clmdQpngYeoEotEhSZLVpmGtvvQ6gcA9AZhkYz/g0igDA8beyJkavV3awZmKQHvbKFqr+hgtXzF3s0q8lrLG1hIwYCzNEuztSnRyJnFp2YT5W+YOt7YEzP30aRrCT0eMSR3NqnmT4fp/tF/5OQbJQLBHMEufXMqAhgNsGpvTv/L+zbeQyTNIlLyZpH2Nll2fZdhjdW0bTyAQPNAkJCTQu3dvAgMDef7553nxxRftUv6uzJNAxo8fX6jLtyDF265dOw4dOuTgVZVvTEJIkiBTo7c6YUFrrgNYQSyApSQATZYme7iA7WUBvJ1auQUgQJCXS44AtOz9o9UbuJ5obI9kqwBsV6cK4VXcScnK4pJhMpsPGUtTDW02lK96f0UV9yrWD6rJhL/eg5M/IgPSQtoyKmU07ds15S0HJTcJBIKKz8aNG0lJSWHdunWsXbuW+fPn07BhQ4YOHcqQIUNsTmgtcwEosB43ZwVymbFkRYZaZ7UANPUCdpKXlgXQGAOYnKFBb5BQWOkGTM9xATuyFRwYk2LAXgKwZG7rUN8cC+AD5AK2VQCa2sFZ2g3kRlImOoOEu1JBqI9t7dJ0BjWtmm7j6yML0admEuIZwtInltK/YX+bxiP+AqwbAQmRgAw6v4d358lskMkdEtwtEAgeLPz8/BgzZgxjxozh1q1b/PTTT6xcuZJp06ah09mWDyAEYAVEJpPhoXQiXa1DpdZhbTlIra50LYD+HkpkOYI1OUNDoJdL8QflwmQB9HZwORSl2QJoBxewOQnEtjWbWuY9UC5gK9vAmQjKaQcXb2EMoDkBJNDTJnF18OZBRm4cycUkY8HCl5q/xILeC/B3s7xcRR5OroGt74A2EzyC4JnvoHZnAIT0EwgE1qDVajl27BiHDx/m+vXr+WopW4NdTUBZWRX/y6qiUJJEEK2hdGMAnRRy/NyNVsCkDOvcwDq9gSyt8RxLywVsjySQtJJaAHME4J27xt6PFRl7WQDjLbQAXs2J/6tnpfs3S5vFOzveocPKDlxMukhVz6psen4TPwz8wTbxp1bBH2Nh4+tG8Ve7C7y23yz+BAKBwFJ2797N6NGjCQ4OZsSIEXh7e7N582Zu3bpl85h2+UZVq9UsXLiQzz//nNjYWHsMKSgGUyKIyoZSMKYYQKdSEoBgdAMnZ2iM/YALLvNYILkFbkmLMxeH0o4xgGm5Ml9tIdjHBZnMKEaTMjTmOMqKSMkFoPHc49ItE4CXc1rAWVMCZn/0fl7e9DKXkoyFmIe1GMaCXgvwc/OzcrU5xJ0zunwTL4FMDl2mQsdJUExtNIFAILifatWqkZycTO/evVm+fDn9+vXLU9/YViz+RlWr1cyYMYOdO3eiVCp57733GDBgAKtWreKDDz5AoVAwceLEEi9IYBklqQVoKgOjLCUXMEAVDxdAZXUiSHpODUAXJ7lZoDkK+5aBKZkF0MVJQYCnCwnpamJSsyu1AAzyMsUAWugCtiIDOFObyYf/fMiCQwuQkAj1CmX5k8t5ov4TNq0VSYITPxiTPXTZ4FXV6PINf8y28QQCQaVnxowZDBo0CF9fX7uOa/G307Rp01i2bBndu3fnwIEDDBo0iJEjR3Lo0CHmz5/PoEGD8nToEDgWswtYU0EsgF62ZQKXVg1AAKVdk0BKFgMIEOrjSkK6mjt3s2hW3afEayor0uxlAbTABWwwSFyNtywD+L/o/xi5cSRXkq8AMOKhEXzZ60t8XX1tWifqdPjzLTj7m/F53e4wcBl4FN0dRCAQCIpi9OjRAFy5coWrV6/SqVMn3NzcbCoDlxuLv1XXrVvHDz/8wFNPPcXZs2dp3rw5Op2OU6dOiSy2MsAkAE2WJmsw1QF0sjIbtyQEmLuBWFcLsLRqAIL9LIAGg2TOXC6JcA31dePUrbvcqeClYFIzS2gBzIkBTM/WkaXR46Ys/IfmnbtZZGn1OCtk1CykZmCmNpOpu6by9eGvkZCo5lWNb/t9S596fWxaHwAxp40u3+SrIFNAt/9B+zehlDLtBQLBg0tSUhLPPfccu3fvRiaTcfnyZWrXrs2oUaPw8/Pjiy++sGlci7+dbt26RevWxir1TZs2xcXFhYkTJwrxV0Z4lcQFnJME4miXam5srQVorgFYKhZA+2QBGwt0G/9fkszle5nAFbsUTEldwF4uTrg5K8jS6olPz6ZmFY9C9zVlAIdX8SjQwv3vjX8ZuXEkV1OuAvDyQy8zv9d8fFxttLBKEhxbAdumgl4N3tXh2ZVQo41t4wkEVmAwGEhNTS12P19f3zxNFQQVi4kTJ+Ls7Ex0dDSNGjUybx88eDCTJk1yvADU6/V5+u06OTnh6WlbkVVByfEogQA0u4BL8QMhwMZ+wOYagKVoASypC9iUAaxUyM1j2oKpFmBFtwCWVADKZDKCvF24kWQsBm2JALzf/ZuhyWDqrql8c+QbJCSqe1fn237f0rtub5vWBED2Xdg0Ac5vMD6v3wcGLAZ3G8vFCARWkpqayvzNJ3H1KLxfeHZGOpOebIm/v3hfVlR27NjB9u3bqV69ep7t9erV48aNGzaPa/G3qiRJjBgxwpx5kp2dzdixY/HwyPthvH79epsXI7AckwBU2VIGppR7AUPJLYC2dtSwBlMh6JK6gO91AXEqkYVcWADvEezlmiMAi74WVwtIANl7fS8vb3qZaynXABjVchRf9PzCdqsfwO0T8NtISLkOcifoPhPajQPhERGUMq4eXnh4+5b1MgQOJCMjA3f3/CEtycnJJcoGtlgADh8+PM/zF1980eZJBSXH09QP2KYsYKMFUFmqZWBs6wesyskC9ipVC2DJXMCmuMWSJIDAg2EBzNbqzRbVklwPS4tB57YAqjQqpvw9hYVHFwIQ5h3Gd099R886PW1eB5IEh5fBjg/BoAWfGjBoFVR/2PYxBQKBoAg6duzIDz/8wKxZswCjV8RgMDB37ly6du1q87gWf6uuWrXK5kkE9sdsAbQpC7gMLIBe9wSgNZlLpRkDaK8kEFPWa0kzl039gOPSstHpDaWatW0vTNdCLiuZiLekGLQkSVzOEYAp2gs0XzKaqNQoAMa0GsPnPT/H28Xb5jWQlQIbx8OFzcbnDZ+E/gvB1lqBAoFAYAFz586lW7duHDt2DI1Gw3vvvce5c+dITk5m//79No8rWsFVUEoWA1i6nUAAqngYYwA1egNpWTqL24KVZgygvQpBl7QGoIkATxec5DJ0Bon4dLVZEFYkTO5fbzdn5CXIOg/yKr4UTFKGJifjWOLlLU8gydTU8KnBiqdW0L12d5vnBuDWMVg3Eu5Gg0IJPWfDo2OEy1cgEDicpk2bcunSJRYuXIiXlxcqlYqnn36acePGUbVqVZvHrXgmBQFQwkLQhtLtBQzg6qwwW4ASrIgDrJAWwOySdQExoZDLCPGp2G5ge8T/wT0LYFHFoH+N2AeAVhaHJFMztvVYzr52tmTiz2CAA9/Ayl5G8ecXDqN2QJtXhfgTCCoA+/bto1+/foSGhiKTydiwYUOe1yVJYtq0aVStWhU3Nze6d+/O5cuX8+yTnJzM0KFD8fb2xtfXl1GjRqFSqfLsc/r0aTp27IirqythYWHMnTs331rWrVtHw4YNcXV1pVmzZmzdurXY9Wu1Wrp160Z8fDwffPABv/76K1u3bmX27NklEn8gBGCFpURJIDpTHcDSvf333MCWC0CzNa0SWgAhb0/gioi9BOC9GMD81yFdnc7YzWOZvP1LAJyVifz90t8seXIJXi6FZ0cWS2Yy/PR8TryfDpoMhFf3QWhL28cUCASlSkZGBi1atGDRokUFvj537ly+/vprli5dyuHDh/Hw8KBXr15kZ9/7rBk6dCjnzp1j586dbN68mX379jFmzBjz62lpafTs2ZOaNWty/PhxPv/8c2bMmMHy5cvN+xw4cIAXXniBUaNGcfLkSQYMGMCAAQM4e/Zsket3dnbm9OnTJbwKBSMEYAWlJEkgWrMFsJQFoA3FoE2dQErHAmjqBFKyJJCS9gHOTdWcRJAYYQEEIP4+C+Df1/6m6ZKmLDu+DGdDGADDW/emW+1uJZqP6EOw9DG4vB0ULvDEfHh2FZQkc1ggEJQ6ffr0Yfbs2QwcODDfa5IksWDBAj788EP69+9P8+bN+eGHH7hz547ZUhgZGcm2bdv47rvvaNOmDY899hjffPMNP//8M3fu3AFgzZo1aDQaVq5cSZMmTXj++eeZMGEC8+fPN8/11Vdf0bt3b959910aNWrErFmzaNWqFQsXLiz2HF588UVWrFhhnwuSCxEDWEEpSQygzhwDWLouLGM/YOtKwdyLASyNMjD2cgHbr3RNRS8FkzsGsCSYBGC6WkeGWoeeTN7Z8Q7fnvgWgHDfcBorBnDuloHGVUuQlGEwwP4F8M9skPRQpS4MWg0hzUq0foFAUP6Iiooi9v/bu+/wJqv2gePfJE3S3VKgiy0gs8oSrCigIshG3ANZgii8IigCioKoLAURRZHt+/5AXIgKiAKyRRAEkSl7tmWU0t2s5/dHmrSlK0nTJi3357p6yZM846SP7XP3PufcJz6ejh1zhomEhITQpk0bduzYwRNPPMGOHTsIDQ2lVaucmf4dO3ZErVazc+dOHnroIXbs2EG7du3y1Eru3Lkz06ZN49q1a1SqVIkdO3YwatSoPNfv3Llzvi7pgphMJhYtWsT69etp2bJlvvJ7uQNNZzgUAP74448On7Bnz54uNUQ4J0Bn6wIuH2sBA1QJcr4YdGqme2bUOsJ9XcC2oKfkba6WnQG8UE4zgCVdBs4mUO+Dv05DusHMioMbeGPzYM4lnwNg2B3DmNpxKg/M2AlkFrsGcKFSL8P3z8OJDdbtmMeg+0woSTeyEMLtUlJSSE5Otm/r9XqX6uHFx8cDEBERkef1iIgI+3vx8fGEh4fned/Hx4ewsLA8+9SpUyffOWzvVapUifj4+CKvU5QDBw7QokULAP79998875X6WsC9e/d26GQqlQqzuWTdZ8IxtkkgWSaL0yVCjB7KALpSDDq1TFcCsXUBe2MGsHwGgO7qAgaoEqjlbKKZwStfIUtzjjqhdVjUaxEdancgNctkz5LWq+pCwHZ6G3w7CFLjwccPuk6H5n1loocQXqhx48Z5tidMmMDEiRM905gysHHjxlI5r0NPVYulZA9E4X4BuQKitCwzIf6OB4Amj40BtAWATowBdOOEiuK4OwPojjbnjAEsn13AyW4KANceX8uZlMOouBWNUpn/tP4PU+6fQoDO2hVyIrv+X5VAvcMlhgCwmGHrDNg0BRQLVGlg7fKNaFzsoUIIzzh06BDVqlWzb7u6GkZkZCQACQkJeWbUJiQk0KxZM/s+ly5dynOcyWQiMTHRfnxkZCQJCQl59rFtF7eP7X1PkEkg5ZTOR21fycOZYtAWi4LZ45NAHMsAmi0KaQZrRrks1wJ2VyFod0wCsc0CvppmINNY/rLrJc0AJmUmMeiHQXRZ2oV0i3XA9UutxjO7y2x78AfYC0DXCy98neB8UhLgfw/BxveswV+zp2HIRgn+hPByQUFBBAcH279cDQDr1KlDZGQkGzZssL+WnJzMzp07iY2NBSA2NpakpCT27Nlj3+e3337DYrHQpk0b+z5btmzBaDTa91m3bh0NGjSgUqVK9n1yX8e2j+06nuDSUzUtLY3Nmzdz9uxZDIa82ZyXXnrJLQ0TxQvQazCkW5yaCGLMlc0ty5VAwPku4NzjG8tiFrDOzUvBuSMDGOqvxU+rIcNoJu56JnWqOBHgeIGSBIA/H/uZwT8N5kLKBVSouC2qDifOQ6BPtXz72paAqx/uYPfvyU3w3WBIuwRaf+ss32ZPOt1GIYR3S01N5fjx4/btU6dOsW/fPsLCwqhZsyYvv/wy7777LvXr16dOnTq8+eabREdH24e+NWrUiAcffJDBgwczd+5cjEYjw4cP54knniA6OhqAp556irfffptBgwYxZswYDhw4wEcffcSHH35ov+6IESNo3749M2bMoFu3bixfvpzdu3fnKRVT1px+Qu3du5euXbuSnp5OWloaYWFhXLlyBX9/f8LDwyUALEMBeh+upRudmghimwACoC3rOoC2ADDFsS5g2+fSadT28Xmlyb4WsNE9dQDdMe5NpVIRFerLyctpxCVllNsAMNSJ70VSZhKjfhnF4n3W5SfrhdVjUc9FHDlTjffOHy6wGHTuNYCLZDbB5mmw5X1AgfDG1i7fqg0cbp8QovzYvXt3nvVybTNx+/Xrx5IlS3jttddIS0tjyJAhJCUlcffdd7N27Vp8fX3txyxdupThw4dz//33o1arefjhh5k9e7b9/ZCQEH799VeGDRtGy5YtqVKlCm+99VaeWoF33XUXy5YtY/z48bz++uvUr1+flStX0rRp0zL4LhTM6QBw5MiR9OjRg7lz5xISEsIff/yBVqvlmWeeYcSIEaXRRlEIV1YDsZWAAQ9MAskuBJ1hNJNuMKEt5vJluQoI5EwCMZhdDwCNZgsZ2V217hq3GB3ix8nLaeWyGLSzZWBW/7uaIauGcDHlIipUvHzny7x737v4a/1JvHYBKLgY9InLDgSAyXHw3SA4k712Zot+0GUaaMvfEntCCMd06NABRVEKfV+lUjFp0iQmTZpU6D5hYWEsW7asyOvcdtttbN26tch9Hn30UR599NGiG5ytRYsWbNiwgUqVKjFp0iReffVV/P39HTrWUU6ngPbt28crr7yCWq1Go9GQlZVlX/bk9ddfd2vjRNFcqQWYOwOoKcHarK4I0GnsWTZHsoCpWWVXAgZydQGXYKydLfsH7hu3GB1afpeDc7QL+FrGNfqv7E/3L7tzMeUi9cPqs3XAVmZ2nom/1vpLr7Bi0FkmM2eupgFFBIDH1sPcttbgTxcIfRZAz9kS/AkhvNLhw4dJS7P+Xnv77bfzLT3nDk4/obRaLersrsPw8HDOnj1Lo0aNCAkJ4dy5c25voCicK8vB5S4BU5L6Qa5QqVRUCdRzISmDy6lZRAUXHRTYgqmymAACuSaBlCADaJsAEqDTuK3OYnktBZNpNNtnVBc1M3fVv6sY8tMQ4lLjUKFiVOwoJt07yR742YRnZ5ATkvNmAE9fSceiWJcLtO1jZzbBxndhW/ZYnIgYa5dvlXol+3BCCFGKmjVrxoABA7j77rtRFIUPPviAwMCC/8B96623XLqG00/W5s2b8+eff1K/fn3at2/PW2+9xZUrV/jf//7n0b7sm5Ery8GZzJ6ZAWxTJcgaAFonghQ9XqssawBCrjGAJguKorgUIKe4sQagTU4GsHx1AduCYbUKAnX572FiRiIvr32Z/+3/HwC3Vr6Vxb0Wc1eNuwo8X3h2BjDNYCY1y2T//8I2/q9ueGDee3b9vLW237k/rNt3PAed3gOtL0II4c2WLFnChAkTWLVqFSqVip9//hkfn/y/R1UqVdkFgJMnTyYlJQWA9957j2effZYXXniB+vXrs2jRIpcaIVzjymogtlnAPmXc/WtTNbsUzFUHagGWZQ1AyBkDqCjWWomujJF05yogNuU1A5iUa/yf+ob/3348+iPPr3qe+NR41Co1r8S+wtsd3saviC7ZQL0PgXofUrNMXErOJLCq9Q+IAieAHF0LK4dCxjXQB1u7e5vkXwtUCCG8UYMGDVi+fDkAarWaDRs25FuRpKScfkrlXg8vPDyctWvXurVBwnGujQG0BoC28W5lzZn1gMs6A5j7e5JlsriUJU22F4F2ZwbQGhS5KwNoMFlQq0p/KcCCxv9dTb/KiLUjWPrPUgAaVmnI4l6LubP6nQ6dMzxYT+plEwnJWdxiCwBzTwAxGWDD27Aje4H1qGbw6GIIu8VNn0oIIcpWaS3GUTZPVlEqXJsFnL0OcBmXgLFxZj3g5DKeBZwnADSaXQo8k0sha2nrAk7NMpGcaSxRgem0LBP3zdhEsK+WZYPvpOqNY+bc6PoN6wCvPLKSoauGkpCWgFqlZvRdo5nYYSK+Po53yUYEWUvi5J4JfCzB2iPR1D8JFg+BC7utb7R5AR54G3xK7zMKIURZOHHiBLNmzeLw4cOAdTm8ESNGULduXZfP6fRTqk6dOkWOjTp58qTLjRHOcWUSiG2CQ1kXgbaJzB7HFedASRN7GRi9+7JpRdGoVWg1KoxmxeWJIO5cBcTGX+dDiJ+W6xlG4pIyCY50/dx/n0siITmLhOQsnl20i+VD7nRLvcKC2DKAfjqFp757ii8PfAlAoyqNWNJ7Ca2rtXb6nOHBeSeCmC0KJ6+k0Un9J7HrF0HWdfANgV6fQqPubvokQgjhOb/88gs9e/akWbNmtG3bFoDt27fTpEkTfvrpJx544AGXzut0APjyyy/n2TYajezdu5e1a9cyevRolxohXFOSSSA6D00CqVbJ2p15/lrx49nKugwMWL8vRrPZ5WLQ7lwFJLeoEF+uZxi5eD2DBpEOrnZRgIMXk+3/PhyXzOAvdvPFwNb46dxfaNsWAG4/v54LcV+iVql57a7XmNBhglNZv9xuLAVz/so1xrGYAbpfIAuo1goeWQSVarnlMwghhKeNHTuWkSNHMnXq1HyvjxkzpuwCwMKKPc+ZM4fdu3e71AjhGvsYQCfWAjZ5OANYvZK1tMeFa+nF7msbA1iWAaBeqyHNYHY9A5jpXOFjR1UL9eNIfEqJawEevHgdgO63RbH538vsOp3I8GV/MbdvS3c00+5y2mUW7vkSuJ0M81WaRDZhca/F3FHtjhKd114KJiULEk9S6cu+DPA5YH0zdjjcPwF8dCVsvRBCeI/Dhw/z9ddf53t94MCBzJo1y+Xzui0N1KVLF7777jt3nU44IKcL2PEA0N4F7KExgNWyJzQkZ5rsM2YLU9Z1ACEnM+p1GcDscYBxJZwIYssAPtyiOgv73YHeR82GI5d47dv9WCyFV8t3xreHvqXJp004fOkMAHfWiGHPkD0lDv4gJwNYJ+FX+Lw9wdcOcE0JZG70ZOj8ngR/QogKp2rVquzbty/f6/v27SvRzGC3PaW+/fZbwsLC3HU64YCSTALRemgWcIDeh1B/LUnpRi4UE8yU9SxgAL3WVgzatdVA7GVg3DgGEHJKwVwsQSmYDIPZvmRak+hgwoN9+fTpFgz53x6+33uBIL2GFiVo46W0SwxfM5xvDn0DQF3f6pjSoGejjujdNBEjwh/e8VlE36T1AJzyj+GpxCE8fotjs4iFEKK8GTx4MEOGDOHkyZPcdZe1Tur27duZNm2afW1jV7hUCDr3JBBFUYiPj+fy5ct8+umnLjdEOC+nDIzjwYopezq51kN1AAGqV/LLDgCLDmbKei1gKHkGMDmjdDKA1eylYFwPAI/EJ2NRoEqg3l5U+f5GEXzw6G2M/Opv/vvHWa7UUNHNhXN/ffBrhq0ZxpX0K2hUGsbdPY7zZzqx8egV900yuXKcZr/0pbXPIQCUu0cx+mgH4hJTi14DWAghyrE333yToKAgZsyYwbhx4wCIjo5m4sSJvPTSSy6f1+mnVK9evfIEgGq1mqpVq9KhQwcaNmzockOE82yTQJzrAvbsSiBgDWYOXEjmQlImVYrYzz4GsIxmAUNOBtC2hJmzUrJKKwPo+OzpwhzI7v5tEh2c5/WHmlcnKd3I2z8dYs05Da13naN/W8fq5iWkJjBszTC+O2wd/hETHsOS3ktoEdWCRz77HSh+HWCH7P8GVr2MzpDKFSWYUcYX+OTu0Rzd9htQxBrAQghRzqlUKkaOHMnIkSPtC3EEBbk+GdDG6QBw4sSJJb6ocA9beZS0LJPDS5d5ehII5EwEuZiUUWQAmOKBDKBtNRBXA0BbBtCdK4FATjHouOuZLi9Tdyh7AsiNASDAgLZ1uJqSySebTvL2qsOEBfrS8/boQs+lKApfHfyK4WuGczXjKj5qH16/+3XeaPcGOo11HF5BhaCdZkiHtWPgr/9at2vdzWNnnuGkJZgD56+TkmlCrYI6VQJcv4YQQpQT7gj8bJxOA2k0Gi5dupTv9atXr6LRuL+UhChcQHYG0GRRHA5YbCuBeDoDCBQ5BtBiUTwyBtDeBWwq2RhAd64EAtbJDyqVdRWPq2nFL6NXkIP2DGBIge+/dF9d7omwoCgw6qt9bDqa/+ccrFm/R755hCe/e5KrGVe5PeJ2dj23i7fvfdse/EHepeBccvkoLLg/O/hTQfsx8OwPqIKiANh+4goANcP87YG7EEIIxzgdBShKwTMFs7Ky0OlkBl5Zsq0FDI53AxvtXcCeywDaagEWNQYwd2mbsi0Dkz0JxIUMoKIo9qylu7uAdT5qqgZaJ1K4Mg7QaLZwJN7adVBQBhCs3Qx96ljoHhOJyaLwwv/9xZ4zifb3FUXhy3++pPGnjVlxeAU+ah8mtp/IrsG7aB7VPN/5SpQB3LcM5nWAS4cgIByeXQn3vg4aH/tM4N9PXAWk+1cIIVzh8JN19uzZgPUhsWDBAgIDc37pms1mtmzZImMAy5harcJfpyHdYCYty0SVwOJnWuZ0AXsuA1g9dwBYs+B9bAGtVqNCX4YzlnMygM4HgBlGM6bsUiqlEbRGhfpxKSWLi0mZ3FbduWNPXE7FYLIQqPehZph/ofupVTCtT1NSssxs/vcyAxb/yddDYwkNTOeF1S+w8shKAJpFNmNJryXcHnl7gefJNJrtQXSIvxMBoCENVr8Kfy+zbtdpD33mQ1CEfRdbALj/vLVLu64EgEII4TSHn1IffvghYM0CzJ07N093r06no3bt2sydO9f9LRRFCtD7kG4wO58B9OQs4FBrAJKYZqSwCcypuWoAujLezVV6rfX/a1cygLbsnyY7MHe36BBf/j4HcS6Ugjl4wdr92zgqGHUx917no2buMy15ZuFO9py5xqOfb+aibiSJhhNo1VrebPcmY+8ei1ZTeGBny/6pVRCoc/DXTMIh+KYfXPkXVGroMA7ueQXUeb+XtuXgzNnBdv1w942JEUIIb2I0GnnwwQeZO3cu9evXd+u5HQ4AT506BcC9997LihUrqFSpklsbIlwTqPfhckqWw6VgjBbPjwEM9vMhSO9DSpaJa1kF75OSVfYTQKBkGUDbOsBBvqUTtOaeCOIs2/i/xoV0/97IT6dh8sM16PXpcVIyKqPNeo7mtb5lSe9F3BZxW7HHX881/q+4gBNFsY7z+/k1MGVCUBQ8vABq313g7hFBeZeRky5gIURFpdVq2b9/f6mc2+koYOPGjRL8eZEAJ9cDthWC9mQXsEqlso8DvJZVcHCQkwEsuxIwkLsMjPOTQJJLaRUQG1spmOLqJxbEtgRc02oFTwDJTVEU/vf3/4hdfDsnlDFYSMfXEkPfW/7PoeAPnBj/l5UCKwbDTy9Zg7+698PQbYUGf5CTAbSpW1VmAAshKq5nnnmGhQsXuv28Tj+pHn74YVq3bs2YMWPyvD59+nT+/PNPvvnmG7c1ThTPNhHE8S5gWwbQc13AkLO27dVCMoA5NQDLNgNoG2/oWhdw6dQAtLFnAJ0MABVF4VBcwTUAb5RoTOShbx5izfE1ALSo1oJ+t9Zg5tqrfLLxJO1uDadlreJX/Lmebv1ehBYVAMbth28HwNXjoNLAfeOh7ctQzDKFtjGAAJHBvm6fcS2EEN7EZDKxaNEi1q9fT8uWLQkIyPtH78yZM106r9NP1y1bthRYC7BLly7MmDHDpUYI1zm7HJzRCwpBQ85EkMIygLZgqsy7gH1K0AVcRhlAZ7uAzyVmkJJpQuejLrS7VFEU/rv/v4w4MoI0cxo6jY4J7Scw+q7RaDVaTiXs4/u9F3jpy32sGXFPsZm960WVgFEU2L0Q1r4O5iwIrgaPLIKaji3nlrsLWLp/hRAV3YEDB2jRwrpQ57///pvnvZIMN3L6SZWamlpguRetVktycrLLDRGusS0H52wG0JOFoCGnFExiYWMAM8u+BiDkFIIuSQawtDJStvqJCcmZmMwWh7vxD2R3/zaICCow8L+QfIEhq4aw5pg169cyqiVLei+haXhT+z6TejVhz5lrnE1M5/Xv/+GTJ5sX+Yun0C7gzOvw0wg4+L11+9YHofdn4O/4OuK5u4AlABRCVHQbN24slfM6nQaKiYnhq6++yvf68uXLady4sVsaJRzn7HrAtjIwOg9nAKvZZgIXNgYwq3SzaYXR+5RgDGBG6dQAtKkSqEerUWFRICGlkMi5AAcLWQFEURSW7FtCk0+bsObYGnQaHX2j+rK139Y8wR9Yg9rZTzbHR61i9f44vtl9vshrFhgAXtwLn7ezBn9qH+j0Hjy53KngD8BXqyE4+/8LKQEjhLhZHD9+nF9++YWMDOswoMLqMjvK6afrm2++SZ8+fThx4gT33XcfABs2bODLL7+U8X8eYFsPOHfh5KIYs0tn+BQzzqq05XQBF/x+qgeWgQP3jAEsraBVrVYREezL+WsZxCVl2DOCxTlYwBrA55PPM+SnIfx8/GcA7oi+g/nd5nP6z9P4qAtuf7MaobzSqQHT1h5hwo8HaVm7EnWrFhyA5QkAFQV2zYNfx4PZACE14dHFUL2Vw5/9RnWqBvL3uSRiHJjUIoQQ5dnVq1d57LHH2LhxIyqVimPHjnHLLbcwaNAgKlWq5PLwO6ejgB49erBy5UqOHz/Oiy++yCuvvML58+dZv349vXv3dqkRwnVOdwGbvKsL+LpRVeB4O09NAinZGMASLn3mgOgQ6/ftohPjAHNKwISgKAqL9i6iyadN+Pn4z+g1eqZ1nMbvg36ncdXiM/jPt7uFtvUqk2E089KXewvNlNoCwKo+GfDVM9YSL2YDNOwOQ7eUKPgDmPV4Mz7v25JmNUJLdB4hhPB2I0eORKvVcvbsWfz9cwr5P/7446xdu9bl87r0dO3WrRvdunXL9/qBAwdo2rRpAUeI0uLsJBDbShWe7gKuHKDDV6sm02gh/nom9fzylvZI8cA6wJC7C9j1QtDBpZi1jA61ToBwdDm4SymZXE7JQqWCIP9kuix9kl9O/AJAm2ptWNxrMY2qNgLAaDYWez61WsXMx5rx4KwtHLyYzPtrjzK+e/7A8XqGkWaq4zy251XIuAhqLXR6F9o8D26okVinSgB1qkj5FyFExffrr7/yyy+/UL163iWg6tevz5kzZ1w+b4mjgJSUFObNm0fr1q25/faCl4USpSfA6VnA3pEBVKlU9mxWQXXtcrqAy7gOYIkmgZTuGECwLgcHjpeCsWX/wgJNtFoQwy8nfrFn/bYP3G4P/pwREezL+49Yf9YXbDvFpqOX8u6gKLS7spxvdG8TkHERKtWGQb/CnUPdEvwJIcTNJC0tLU/mzyYxMRG9vvglYAvjcgC4ZcsWnn32WaKiovjggw+47777+OOPP1xuiHCN67OAPZsBBKgWWnhhY3sZGI91AbsyCaR0xwCCdTk4cLwL+PeTZwE4m76NFEMKd1a/k31D9/Fa29fQqF1frq5j4wj6xdYC4NVv/uaybVJKeiJ8+QT9UxegVZm5UrMrPL8FqrVw+VpCCHEzu+eee/jvf/9r31apVFgsFqZPn869997r8nmdelLFx8ezZMkSFi5cSHJyMo899hhZWVmsXLlSZgB7iH0SiMOzgG1dwJ7PxNjGAV5Iyh/MeHoWcEkygKVZmDhnObiiM4CKojD/r/nM2X4OHXdi8TnLjE4zGNFmRIkCv9zGdW3EzlOJHIlP4ZVv/mbJfWbUK56D5PNkoeUd4zM80WkiVXxlooYQQrhq+vTp3H///ezevRuDwcBrr73GwYMHSUxMZPv27S6f1+E0UI8ePWjQoAH79+9n1qxZXLx4kY8//tjlCwv3sK0E4mgXsMGWAfTwLGCAaiGFj2dL9VAdQPdMAim9NkfZJoEUEDTbnEk6Q6f/68Tzq55HZa4JwKe9xjEqdpTbgj+wlmP5+Mnm+GmhyYmF8EU3SD4PYXV5zPQO/2d+gBD//DVDhRBCOK5p06b8+++/3H333fTq1Yu0tDT69OnD3r17qVu3rsvndfhJ9fPPP/PSSy/xwgsvUL9+fZcvKNzL2S5gWwZQ6+MFAWB2BvB8AcFMiscygCUfA1i6GUBr0JyYZiDTaMZXmxPQWRQL8/bMY/S60aQaUvHXVEarRAPQuWHpZOjrB2axIWIO0Ve2gwJJdXvj+9BH/P2u9a/SUH9Zpk0IIUoqJCSEN954w63ndDgK2LZtGykpKbRs2ZI2bdrwySefcOXKFbc2RjjP+VnA2WsBq72gCzjUls3KmwFUFMUe0JaXpeDMlpw2l+Ys4BA/LX7ZQV/uJeFOXTvFA/97gBdWv0CqIZW7a97NF903ANbvc2hpZOJOb4e5dxN9ZTsGlY7XjIN5KL4/cZnWoE+jVpV5BlcIISqia9eu8cEHHzBo0CAGDRrEjBkzSExMLNE5HQ4A77zzTubPn09cXBzPP/88y5cvJzo6GovFwrp160hJSSlRQ4Rr7LOADWYsluKrghuyM4DeMAnEls2KT86yr1ACkG4wYytwHqQv61nArk0CsXVZQ+lmAFUqVZ5SMBbFwqd/fkrMZzH8duo3/Hz8+OjBj9jcfzPXU62FnxvfsAJIiVnMsPl9+KI7pMRBlVvJ7L+erYFdOHU1ndHf/A1YA+GSrFMphBDCOum2du3azJ49m2vXrnHt2jVmz55NnTp12LJli8vndToKCAgIYODAgWzbto1//vmHV155halTpxIeHk7Pnj1dbohwTe4MS7qx+KDFFmhpvWASSHigHo1KwWxRiE/OyWbZMmkatQpfbdkGqq7WAbSN/9P7qO1ZxNJimwjy98Wz3P/f+xm2ZhhpxjTa1WrH/hf281Kbl1Cr1IUuAVciKQnwv4dg47ugWOD2p2DIJoJr3c6HjzdDrYLdZ64BBawDLIQQwmnDhg3j8ccf59SpU6xYsYIVK1Zw8uRJnnjiCYYNG+byeUv0pGrQoAHTp0/n/PnzfPnllyU5lXCRr1aNrTfXkW5g+xhAL8gAqtUqKmX3TF64ltMNnJJrAkhZZ5Bc7QIui1VAbCKzJ89M2DCLTac34a/1Z/aDs9nYbyP1wurZ9ztkXwLOTbNwT26CuXfDqc2g9Yfen8FDn4HOWpD5zlsqM/zenOtLACiEECV3/PhxXnnlFTSanDHfGo2GUaNGcfz4cZfP65YoQKPR0Lt3b3788Ud3nE44QaVSOTURxF4H0AvGAAKE+VoD0vN5AkDP1ACEvJNAnFloO2cCSOm2+UTiCX499RUAFlMI7Wu1558X/uE/bf6DWpXz45xpNHPsUirghgygxQwbJ8N/e0PaJQhvDIM3QrOn8u360v31aVmrEkDpjDsUQoibTIsWLTh8+HC+1w8fPlyiBThkhHYFEKj3ISXT5FAG0GibBOIFs4CBnAxgrokgnqoBCOTpvjWYLfaAsDilvQqIRbEwZ9ccxm4YiyqjLVVoS0zl9vzW76M8gZ/NvwkpmC0Klfy1RGVnDF2SHAffPQdntlm3WzwLD04DXf6q9GAdW/rJU82Z9vMRHmtVw/XrCiHETWz//v32f7/00kuMGDGC48ePc+eddwLwxx9/MGfOHKZOneryNSQArACcygCasruAvaAOIECY3pYBTLe/llpG2bSC6HMHgCbHA8DSXAXkeOJxBv4wkK1ntwLQJrIa8edAS9UCgz/IWQKuSXSI693ox9fDiuch/QroAqH7LLjt0WIPiwrxY9YTzV27phBCCJo1a4ZKpcrTE/Xaa6/l2++pp57i8ccfd+kaXhEFzJkzh9q1a+Pr60ubNm3YtWuXQ8ctX74clUpF7969S7eBXi5nPWAHJoHYM4De0gVs/W/uDKCtBqAnuoB1ucZGOjMO0NZt7c4MoEWx8NEfH3HbZ7ex9exWArQBfNr1U/73yEeAdRZwYd3U9gkg1Vzo/rWYYP1E+L+HrcFfRAwM2exQ8CeEEN6idu3aqFSqfF+2iRMdOnTI997QoUPznOPs2bN069YNf39/wsPDGT16NCZT3mTLpk2baNGiBXq9nnr16rFkyZISt/3UqVOcPHmSU6dOFfl18uRJl6/h8QzgV199xahRo5g7dy5t2rRh1qxZdO7cmaNHjxIeHl7ocadPn+bVV1/lnnvuKcPWeqec5eAcGQOYXQbGWzKAOmt7ck8Csa8CUorlVAqjVqvQadQYzBanAsBkWxewm1YBOXb1GAN/HMi2s9au1/vq3MfCngupHVqbdIP1WmkGM8mZpgInWxx0cQKIr+Eqmv/1gvM7rS+0GgSdJ4O2BN3IQgjhAX/++Sdmc05i5MCBAzzwwAM8+mjOH7ODBw9m0qRJ9m1//5zhLWazmW7duhEZGcnvv/9OXFwczz77LFqtlsmTJwPWQK1bt24MHTqUpUuXsmHDBp577jmioqLo3Lmzy22vVauWy8c6yuMB4MyZMxk8eDADBgwAYO7cuaxevZpFixYxduzYAo8xm808/fTTvP3222zdupWkpKQybLH3sS0H58wkEG8oAwNQSW/978WkTCwWBbValVME2kNFhPU+1gDQmdVAbBnAktYANFvMzN45mzd+e4MMUwaBukA+eOADhrQcYu/K9df5EOqvJSndSNz1jHwBoNmicDjOFgA6ngFUHfuVe4+MR21OA30w9PgImvYp0ecRQghPqVq1ap7tqVOnUrduXdq3b29/zd/fn8jIyAKP//XXXzl06BDr168nIiKCZs2a8c477zBmzBgmTpyITqdj7ty51KlThxkzZgDQqFEjtm3bxocffliiAPBGFy9eZNu2bVy6dAmLJe+z6aWXXnLpnB4NAA0GA3v27GHcuHH219RqNR07dmTHjh2FHjdp0iTCw8MZNGgQW7duLfIaWVlZZGVl2bdtBauNRiNGo7GEn8A7+GfXykvOyCr2M9kCQJVi8fjnNxqNhOpBo1JhMFu4eC2ViGBfrqdb75e/VuWRNmp9VJAFaRlZGI2OzWRNSjcAEKBVu9zmf6/+y+DVg9lx3vr//v2172dut7nUCqmVr8shMtiXpHQj566mUreyX573jl1KJdNowV+noXqwrvj2mI2oN72Lzx9zrJsRt2F5eCFUqgMV5GekvLHdM0//jArvvhdGoxFFMWOxFD78R1HM9uedI/vnPsb2b0f3d+UaznxfbfumpKSQnJxsf12v16PX64s81mAw8H//93+MGjUqz7jopUuX8n//939ERkbSo0cP3nzzTXsWcMeOHcTExBAREWHfv3PnzrzwwgscPHiQ5s2bs2PHDjp27JjnWp07d+bll192+HMVZ8mSJTz//PPodDoqV66cp/0qlap8BoBXrlzBbDbn+eYCREREcOTIkQKP2bZtGwsXLmTfvn0OXWPKlCm8/fbb+V7fsmULhw4dcrrN3uhqvBpQ8/eBo6xJzj9V3EZRwGTWACo2b/yNYC+o0qFRQbDWwjWDim9//o06QXD4hPXzxJ09yZo1J8q8TRaj9Xu0cctWTgQ6dsyxU9Y2nz1xlDXpBf+/WxizYuanyz+xLG4ZBsWAn9qPAdUG8EDIAxzcfpCDHMx3jCbLer1123eTfjzvOMDdl1WAhgi9ibVrfy7y2n6GK7Q6NYewdOv3+UTVThyKfBzLjsNA4f8vibKxbt06TzdBZPPGe5GSksKJC2p8A4IK3SczLYV1mScICgpyaP/cxwBO7e/KNYKCit4vN9vys40b513bfMKECUycOLHIY1euXElSUhL9+/e3v/bUU09Rq1YtoqOj2b9/P2PGjOHo0aOsWLECgPj4+ALjE9t7Re2TnJxMRkYGfn55/0B3xZtvvslbb73FuHHjULtx+JbHu4CdkZKSQt++fZk/fz5VqlRx6Jhx48YxatQo+/aFCxdo3Lgx7dq1o3bt2qXU0rJ16NdjbE04RVTN2nTt2rDQ/UxmC8of6wHo3KkjlTxcp81oNLJu3TrqRoay++x1ajZqTtfbovj1q/1wKZ7mMY3pGlv64yBuNPPoNpIS02nVJpZW2TXtivP1pT2QeJXYlrfTtVm0w9c6cuUIg1cPZudF65i7B+o8wGddP6NmSM0ij9tlPszBXeeoXL0eXR+on+e9/WuPwvEztG1ck65dGxV6DtXRNWhWvY0q8zqKbwiGB2dy4IyWBx54AK1Wijh7ku1nQ+6F53nzvUhMTOTU1pP4B4UWuk96ShIP3HMLYWFhDu2f+xjAqf1duUZYWFiR++V2+vRpAA4dOkS1atXsrxeX/QNYuHAhXbp0ITo65/fzkCFD7P+OiYkhKiqK+++/nxMnTlC3bl2H21Xa0tPTeeKJJ9wa/IGHA8AqVaqg0WhISEjI83pCQkKBffInTpzg9OnT9OjRw/6arS/cx8eHo0eP5rtpN6aGbWljrVbrdT/MrgrODuQyjEqRn8lMTkre31ePVusd8X/1Sv7sPnud+BQDWq2WtOwl7UL89R65R75a66QaC2qHr28btxga4OvQMWaLmZk7ZvLmxjfJMmcRrA9mZqeZDGw+0KGyLdXCrF0UCdnfs9wOx1sLQMdUDy24LaYsWDcBdn6WfbKWqB5ZjDowGs6sqVA/G+Wd3Avv4Y33QqvVolJpUKsLL1elUmnsbXdk/9zH2P7t6P6uXMOZ76lt36CgIIKDHR/ffObMGdavX2/P7BWmTZs2gHXljbp16xIZGZmvKoktXrHFKJGRkQXGMMHBwW7J/gEMGjSIb775ptB5Ea7yaASg0+lo2bIlGzZssJdysVgsbNiwgeHDh+fbv2HDhvzzzz95Xhs/fjwpKSl89NFH1KhxcxaeDdBZf9BSDUVPAjGYcwaOestKIJCztq1tNZBUe1Flz/zvmbMcXPFldWycWQnk8OXDDPhhADsvWLN+D9Z7kHnd51EjxPH/f6NDrN+zi9cz8ryuKErRM4ATT8E3/SFun3U7djjcPwF8dDLeTwhRIS1evJjw8HC6detW5H62oWVRUVEAxMbG8t5773Hp0iV7VZJ169YRHBxs74aOjY1lzZo1ec6zbt06YmNj3db+KVOm0L17d9auXUtMTEy+oHnmzJkundfjKaBRo0bRr18/WrVqRevWrZk1axZpaWn2WcHPPvss1apVY8qUKfj6+tK0adM8x4eGhgLke/1mYi8EnVl0AGhbBxi8Yy1gm+qVrCVGbKVgcmYBe+avbVsxaGdmATuyFrDJYmLG7zOYsGmCPes3q/Ms+jfr73SxZlvQHHc9M8/rF5IyuJ5hxEeton7EDQMYD66EH/8DWcngV8m6lm+DLk5dVwghyhOLxcLixYvp168fPj45Ic+JEydYtmwZXbt2pXLlyuzfv5+RI0fSrl07brvtNgA6depE48aN6du3L9OnTyc+Pp7x48czbNgwe8/i0KFD+eSTT3jttdcYOHAgv/32G19//TWrV69222eYMmUKv/zyCw0aNADINwnEVR4PAB9//HEuX77MW2+9RXx8PM2aNWPt2rX2QZVnz551e793RRNoLwRdXABoDWjUKtB4YQbQVgw6xV4H0ENlYLS2DKDzdQALywAeunyIAT8MYNcFa3dC1/pd+bz751QPru5SG23Lu8XlKp8DOfX/6kcE5axiYsyEX9+APxdYt2u0gUcWQYhr1xZCCHexWCwOl3K7sfyJI9avX8/Zs2cZOHBgntd1Oh3r16+3J51q1KjBww8/zPjx4+37aDQaVq1axQsvvEBsbCwBAQH069cvT93AOnXqsHr1akaOHMlHH31E9erVWbBggVtLwMyYMYNFixblmcDiDh4PAAGGDx9eYJcvWCtsF8UdFbfLO0eXgrN1Aft4UfYPoLq9CzgdRVE8XgfQthpIltGxXzaZRrM9W3hjBtBkMfH+9veZuHkiBrOBEH0IHz34Ec/e/myJ/nKLDPFFpbLe06tpBqoGWf8atQWATW31/66egG/6QXz20Im7R8K9b4DGu8YyCSFuTklJScxctdehWcMPxzg+YcSmU6dOBa6YVKNGDTZv3lzs8bVq1crXxXujDh06sHfvXqfb5ii9Xk/btm3dfl6vCABFydiXgitmDKCtC1jnZQFgZHY2K9NoITHNYA8APbEWMGDPnGWZHQsAbRlLlQoCdTltPnDpAAN+GMDui7sB6Fa/G593/5xqwdUKPI8ztBo1VQP1XErJIu56hj0APGRbAi46GP75Fn4aAYZU8K8MD82D+h2LOq0QQpQ534AgAoJDPd0MrzVixAg+/vhjZs+e7dbzSgBYAQQ6uBawbR1gHy9ZBcRG76MmPMgazBy7lIrZYg1UPZYBtE0CMTo2CcS2Ckigzge1WoXJYmL69um8vfltDGYDob6hzH5wNs/c9kyJsn43ig7141JKFheTMriteigABy4ko8dA1zNT4d/l1h1rtYWHF0Cw4+VphBBCeIddu3bx22+/sWrVKpo0aZJvEkhxs5sLIwFgBRCQvRZwsV3AJu9aBzi36pWswcyR7CXMVCrw1xVdRqC02CeBOJgBzFkHWMs/Cf8w4IcB7InbA0D3W7vzeffPiQ5yf/AVHerLvnPWZfQArqZmEZBygiW62YT/ew5QQbvR0H4MaORHXQghyqPQ0FD69HH/spzyVKgAbJkyg8mC0WwpdIavLQOo87IMIEC1Sv78dTaJownWpfoC9T5uzZY5IycD6GgXsDUDmG5OpOW8BzFajFTyrcTsLrN5OubpUvscUSG2mcDWyTOXt33BT7rx+KuyICAc+syDuveWyrWFEEKUjcWLF5fKeSUArAACcnWVpmWZCC1khQ+jl04CAaiWPRHkcJw1AAz29dwkBdsYQEczgAfirUsmxaWdwKg30rNBT+Z2m0tUUFSptRFyZgJfuXYNVr5Iw31LQQVH/ZrTYOhXEBRRzBmEEELcrCQArAC0GjU6HzUGk4XUIgNAJXt/78sAVq9kDQD/zZUB9BRHM4BGs5Ep26Ywc8MfhDIMH42RpX2W8mTTJ8ske1kt1I9bVecYdWoMmM9hQc2Hxj74t3+NBhL8CSFEhVCnTp0inyknT5506bwSAFYQgXofEk2GIieCmOwBoBdmALMDwHSDtf2eqgEIOWMAi1oJZF/8Pgb8MIB98fsIsjwEQPcG9/NUjPuqvxdJUWiS8AM/6N7Ez2yAwEheMQ3n+8xb+KKa86UShBBCeKeXX345z7bRaGTv3r2sXbuW0aNHu3xeCQAriAC9hsS0oieC5HQBe18GsEalvGsmejIDaCsEXdBKIAazgclbJ/Pe1vcwWUxU9qtMz7rP8NsBCA8quo6V22SlwKpR1Pzna1DBFksMzfp/zcoZ1jpUTaIdXyNTCCGEdxsxYkSBr8+ZM4fdu3e7fF7vSwUJlwToil8NxBYAemMG0LYaiI0nM4D2QtA3BIB74/bSen5r3t78NiaLiT6N+nDwxYPUDLYuz1MmdQvj/4F5HeCfr1FUGt43P0E/wxg2nldQFIgI1lMlUF/67RBCCOFRXbp04bvvvnP5eMkAVhCOLAdnyq6vp/XCMjD+Oh/CAnQkphkACPJoBjB7Ekh2AGgwG3h3y7tM2TYFk8VEFf8qzOk6h0cbP4pKpSI5Iw4o5YkrigK7F8HacWDOguBqqB5eyI9fZaAkZrD+8CUAmkaHlF4bhBClxpkl0UJDQ2WJVMG3335LWJjrQ34kAKwgHFkOzpu7gME6EcQWAHq0C1iTMwbwr7i/6L+yP/9csi6l9kjjR5jTdQ7hAeH2/XPWAS6lADAzGX56CQ5+b92u3xl6fwYBlYkK2cG5xAw2HbEGgNL9K0T55MySaKO6Ny/Rg1+UL82bN88zCURRFOLj47l8+TKffvqpy+eVALCCcCQDaPTiSSBgndW6/7x1KbNSC6YcYBsDePjyMVrP74dZMduzfo81eSzf/rY6gMF+pfDjdHEvfDMArp0CtQ90nAh3DoPsv/6js0vBpGTf98aSARSi3JIl0URBevfunWdbrVZTtWpVOnToQMOGDV0+rwSAFYRtNZA0Q+EzV3PGAHpvBtDGk2MAzyWfAuB00gXMejOPNXmMT7p8QtWAqgXuXyoZQEWBXfPg1/FgNkBITXhkEdS4I89uN46dlAygEEJULBMmTCiV80oAWEE40gVs8uJJIJBTDBo8MwYwy5TFpM2T+GjLeqrwFlqVP988+g2PNH6kyONsGUC3TQLJuAY/DIcjq6zbDbtDr0/Ar1K+XaNyfc9C/LR5gmghhBCiMBIAVhDOdAF740ogYF0OzqasM4B/XviT/j/059DlQ/gqtwNwa+XGPNL4vmKPTc7I7gJ2Rwbw/B74tj8knQW1Fjq9C22ety6OXABbFzBA46hgjy2fJ4QQwr3UanWxv9NVKhUmU+HP/aJIAFhBODMJRKv2ziAhTxdwGWUAM02ZvL3pbab/Ph2LYiE8IJzRrSbwyVowm4v/PimKYv+eB5ckaFUU2DEH1k8Aiwkq1YZHFkO1FkUeZlsPGKT7VwghKpLvv/++0Pd27NjB7NmzsVgcW7K0IBIAVhABzpSB8doMYNmOAdx5ficDfhjA4SuHAXiy6ZPM7jKbi4k+fML2AgtB3yjNYCb720qwn4sZwPREWPki/PuzdbtxL+j5MfgWP6Ejd7d5k2oSAAohREXRq1evfK8dPXqUsWPH8tNPP/H0008zadIkl8/vnZGAcFqgbRJIEUvBeXsZmGBfLVUCresYVwkovWLGmaZMxqwbw12L7uLwlcNEBESw4rEVLHt4GVX8q+SsBexAAGjr/tVqVPYl5JxydifMvcca/Gn00G0GPPqFQ8EfWGceh/pbA8/bqoc6f30hhBBe7+LFiwwePJiYmBhMJhP79u3jiy++oFatWi6fUzKAFYRtJRCHuoC9NAMIMPuJ5py7lk7Nyv7F7+yCP87/wYAfBnDkyhEAnop5itkPzqayf2X7PnqfvIWgi5KSawawU+PvLBb4/SPY8A4oZgirC48ugajbHD8H1vEfHz/ZnLjrmdStGujUsUIIIbzb9evXmTx5Mh9//DHNmjVjw4YN3HPPPW45twSAFYRDK4HY6wB6ZwYQ4K56VUrlvBnGDN7a+BYz/5iJRbEQGRjJ3G5z6dUwf4rdqQygrQagM13WaVfg+6FwfJ11u+kj0GMW6F1bS/ie+gWXpxFCCFF+TZ8+nWnTphEZGcmXX35ZYJdwSUgAWEE4MgbQYO8C9t4MYGnYcW4HA34YwNGrRwHoe1tfZj04izC/givp27pyDWYLFouCuohJMzklYBwc/3d6O3w3CFLiwMcXukyDFv0KneUrhBDi5jR27Fj8/PyoV68eX3zxBV988UWB+61YscKl80sAWEE4VgfQuyeBuFu6MZ03f3uTD//4EAWFqMAoPu/+OT0a9CjyuNxj+QxmC75qTaH72rqAi10FxGKGrTNh02RQLFDlVmuXb0QThz+PEEKIm8ezzz5bqqW9JACsIGxFiNMMZhRFKfB/GpPFu8vAuNP2s9sZ8MMAjiUeA6Df7f34sPOHVCqgmPKNdLkCwCyTBV9t4QGgbRJIkL6IDGDqJVgxGE5usm7f/iR0/QD0MmZPCCFEwZYsWVKq55cAsIKwZQDNFqXQoMVg8u5C0O6QbkznjQ1v8NHOj1BQiA6KZl73eXS7tZvD59Dl+v4UNxEkubgM4MnN1uAvNQG0/tbAr/nTDrdFCCGEKA0SAFYQ/rkCvtQsU4EBoD0D6MWTQEpi65mtDPxxIMcTjwMwoNkAZnaeSahvqFPnUalU6HzUGEwWskyFl9WBnEkg+cYAWsyweRpsng4oULWRtcs33PWFu4UQQgh3kQCwglCrVQToNKQZzKRlmagSmL+OXkUdA5hmSOON395g9s7ZKChUC6rG/B7z6VK/i8vn1GcHgMVlAHPKwOT6UUqOs2b9Tm+1bjfvC12mg650StsIIYQQzpIAsAIJ0PuQZjAXOhHE4OWFoF2x5cwWBv4wkBPXTgAwqPkgZnSaQYiDhZQLo/dRk0LxpWDyrQN8fAOsGALpV0AbYC3vcttjJWqLEEII4W4SAFYggXofLqVkFboaiKkcFIJ2VJohjXEbxvHxro8BqB5cnQU9FtC5Xme3nN9WDLq4ANA+C1gHrH8bts20vhERY+3yrVLPLe0RQggh3EkCwAqkuFqAxnJQCNoRm05vYtCPgzh57SQAg1sM5v0H3i9x1i83ey3AYgNAI5Fc5f5dg+DKHuuLrQZC58mg9SvyWCGEEMJTJACsQAKy1wNOKTQAzO4CVpfPDGCqIZWx68cy5885ANQIrsGCngvoVLeT26+VsxpI0ZNAGqb8wQL9TCpdSQVdEPScDU37uL09QgghhDtJAFiBFLccnMlSfieBbDy1kYE/DuR00mkAhrQYwvud3idYH1wq1ys2A2g2woZJTM6YDSrIqNIUvyf/C5Xrlkp7hBBCCHeSALACKb4LuPyVgUnJSmHM+jF8tvszAGqF1GJBzwV0vKVjqV63yPWAk87CtwPh/J8ALDZ15v7HPqdm5eKLTAshhBDeQALACqS45eCM5awMzIaTGxj04yDOXD8DwNCWQ5n+wHSC9EGlfm3bJJB8GcAjq2Hli5CZhKIPZmjKQH6xtKZ3QECpt0kIIYRwFwkAK5Biu4DLSRmY5KxkXlv3Gp/v+RywZv0W9lzI/bfcX2ZtyDcG0GSAdW/BTmsmkmotSe76Ob98/C9wQx1AIYQQwsvJU6sCCdDZMoAFT1wwloMyMOtPrmfQj4M4e/0sAC+2epGpHaeWSdYvN33uLuDEU/DtALi41/pm7HC4fwJJ143Av/jrNBV6eT0hhBAVjwSAFYhtFnDxZWC8L1hJzkrm1V9fZf5f8wGoHVqbRT0XcW+dez3SHlsAGH3hF9j0LmQlg28oPDQXGlhXGEnJzAAk+yeEEKL8kSdXBVJcF3BOGRjv6gJed3IdQ9cM5VzyOQCG3TGMqR2nEqgL9Fib/NVGJvkspuOBddYXarSBhxdCaA37PvlWARFCCCHKCQkAK5DiJoF4WxmY65nX+eTsJ6zftx6AWyrdwsKeC+lQu4NnG3b1BMNPDSPaxzq+j7Yvw33jQZM30EsuaB1gIYQQohzwjkhAuIU9A2jw/jIwa4+vpfn85qxPtAZ//2n9H/YP3e/54O+fb+HzdkRn/MtVJYivGsyEB97OF/yBdRUQgGA/yQAKIYS3mThxIiqVKs9Xw4YN7e9nZmYybNgwKleuTGBgIA8//DAJCQl5znH27Fm6deuGv78/4eHhjB49GpMp7zN206ZNtGjRAr1eT7169ViyZElZfLwSk9RFBZJTB9B7J4EkZSbxyi+vsGjfIgAidZEsfWwp99W9z2NtAsCYAWvHwp4lAJwLasYjl5+ja2CLQg/JyQBKACiEEN6oSZMmrF+/3r7t45MT9owcOZLVq1fzzTffEBISwvDhw+nTpw/bt28HwGw2061bNyIjI/n999+Ji4vj2WefRavVMnnyZABOnTpFt27dGDp0KEuXLmXDhg0899xzREVF0bmze9amLy0SAFYgtkkghXYBe3gSyJpjaxjy0xAupFxAhYrhdwynbWZb7ql5j0faY3f5X/imP1w6CKig3ausMPchYcOpggtBZ7NnAKULWAghvJKPjw+RkZH5Xr9+/ToLFy5k2bJl3HefNQGxePFiGjVqxB9//MGdd97Jr7/+yqFDh1i/fj0RERE0a9aMd955hzFjxjBx4kR0Oh1z586lTp06zJgxA4BGjRqxbds2PvzwQ68PAKULuAIpahKIoij2MYBlXQfwWsY1BvwwgG7LunEh5QL1wuqxuf9mZjwwA1+Nb5m2JZ+/l8O8DtbgL6Aq9F0B941Hp9UDkGUsPABMzpAMoBBClLWUlBSSk5PtX1lZWYXue+zYMaKjo7nlllt4+umnOXvWWmJsz549GI1GOnbMWVWqYcOG1KxZkx07dgCwY8cOYmJiiIiIsO/TuXNnkpOTOXjwoH2f3Oew7WM7hzeTALACsXUBpxvMWLKDPRtbCRgArbrsbvvqf1fT9LOmLNm3BBUqRt45kr+H/s09tTyc9TOkwcph8P3zYEyDOu1g6DbI7oq2rwVsLj4DKJNAhBCi7DRu3JiQkBD715QpUwrcr02bNixZsoS1a9fy2WefcerUKe655x5SUlKIj49Hp9MRGhqa55iIiAji4+MBiI+PzxP82d63vVfUPsnJyWRkZLjj45YaeXJVILYMIFgnguTOTJksOYGM1qf0M4DXMq7x8i8v89+//wtA/bD6LO61mLY125b6tYt16bC1y/fyEVCpof1YaPcqqDX2XewrgRgLHk8JkCyTQIQQhbBYLCQlJTm0741BiCjaoUOHqFatmn1br9cXuF+XLl3s/77tttto06YNtWrV4uuvv8bPz6/U2+ntJACsQPQ+ajRqFWaLQlqWOU8AaDTlZAB9SjkD+NPRn3h+1fPEpcahQsWo2FFMuncS/lr/Ur1usRQF9v4frBkNpgwIjISHF0Cd/NlIxzKA1i5gGQMohLhRUlISM1ftxTeg6FWMMtNSGNW9eRm1qmIICgoiODjY6eNCQ0O59dZbOX78OA888AAGg4GkpKQ8AXhCQoJ9zGBkZCS7du3Kcw7bLOHc+9w4czghIYHg4GCvDzKlC7gCUalUBOgKnghizJ0BLKUxgIkZifT9vi89l/ckLjWOWyvfyraB2/ig0weeD/6yUmHFEPhxuDX4q3uftcu3gOAPcmcAHQkAJQMohMjPNyCIgODQIr+KCxCF+6SmpnLixAmioqJo2bIlWq2WDRs22N8/evQoZ8+eJTY2FoDY2Fj++ecfLl26ZN9n3bp1BAcH07hxY/s+uc9h28d2Dm8mqYsKJlDvQ3KmKd9EENsMYB+1tRaSu/149EeeX/U88anxqFVqRt1pzfr5ab3gL6D4f6xdvlePg0oD970BbUdCEZlQvY81kC4qA5gsYwCFEMJrvfrqq/To0YNatWpx8eJFJkyYgEaj4cknnyQkJIRBgwYxatQowsLCCA4O5j//+Q+xsbHceeedAHTq1InGjRvTt29fpk+fTnx8POPHj2fYsGH2buehQ4fyySef8NprrzFw4EB+++03vv76a1avXu3Jj+4QeXJVMAGFzAS2LwPn5uzf1fSrjFg7gqX/LAWgYZWGLO61mDur3+nW67hEUWDPYvh5LJizICgaHlkEtYr/y8zWBZxlKnwMYIrUARRCCK91/vx5nnzySa5evUrVqlW5++67+eOPP6hatSoAH374IWq1mocffpisrCw6d+7Mp59+aj9eo9GwatUqXnjhBWJjYwkICKBfv35MmjTJvk+dOnVYvXo1I0eO5KOPPqJ69eosWLDA60vAgASAFU5hy8GVRhHolUdWMnTVUBLSElCr1Lwa+ypv3/s2vj4eLu0CkJkMP42Agyus2/U7Qe+5EFDZocP1xXQBK4qSsxawn/wYCSGEt1m+fHmR7/v6+jJnzhzmzJlT6D61atVizZo1RZ6nQ4cO7N2716U2epI8uSqYwpaDc+c6wFfSr/DSzy/x5YEvAWhUpRGLey2mTfU2JT63W1zcZ+3yvXYK1D5w/wSIHV5kl++N9NqiJ4FkGi3276lkAIUQQpQ3EgBWMDmrgeTtujRkr2jhoy5ZF/CKwyt4YfULXEq7hFql5rW7XmNChwnekfVTFNg1H359A8wGCKlh7fKt0drpU+k01u9jYRlAWw1AtQr7xBshhBCivJAAsIIpbAxgSTOAl9Mu85+f/8NXB78CoHHVxizptYQ7qt1Rgta6UUaSdYbv4Z+s2w26Qa9PwD/MpdMVlwHMmQCiLZVJNUIIIURpkgCwggkqZhKIKyVgvj30LS+ufpHL6ZfRqDS81vY1JrSfgN6n4OKbZe78Hvi2PySdBbUWOr0DbYZCCQIznaboQtDJ9gkg8iMkhBCi/JGnVwVT3CQQHycygJfSLjF8zXC+OfQNAE3Dm7K412JaRbdyU2tLSFHgj09h3QSwGCG0Fjy6GKq1LPGpi80A2iaAyPg/IYQQ5ZAEgBVMoV3AZue6gL8++DXD1gzjSvoVNCoN4+4ex/h2470n65eeCCtfhH9/tm436gk9Pwa/ULec3pYBNJoVzBYFzQ1jJ1MkAyiEEKIck6dXBWOfBXzDJBBHu4ATUhMYtmYY3x3+DoCY8BgW91pMy+iSZ9Xc5uxO+HYgJJ8HjQ46T4Y7nitRl++N9NqciR0GkwW/GyZ62FcBkXWAhRBClEMSAFYwhXcBF50BVBSFrw5+xfA1w7macRUftQ+v3/06b7R7A51GV7qNdpTFAr/Phg2TQDFD2C3w6BKIut3tl7LVAYSCA0BZBUQIIUR5Jk+vCiYwuwxM/lnAhZeBSUhN4MU1L7LisLVo8u0Rt7O412KaR3nRAuVpV+D7oXB8nXW76cPQfRb4Or8guCOsS+ZZhxlaVwPJm+mzlYGRMYBCCCHKIwkAKxhnVgJRFIXlB5Yz/OfhJGYk4qP2Yfw94xl3zzjvyfoBnPnd2uWbEgc+vtBlGrTo59Yu3xupVCr0PmoyjRayTPkngiRnZHcBSwZQCCFEOSRPrwomoJCVQHK6gK1BU3xqPC+sfoGVR1YC0CyyGYt7LaZZZLMya2uxLBbYNgM2TgbFApXrW7t8I5uWyeV1msIDwJRcdQCFEEKI8kYCwAqmuEkgPho1S/cv5T8//4drmdfQqrW82e5Nxt49Fq3Gi4KZ1EuwYgic3Gjdvu0J6DYD9IFl1gS9VgOZJvsqKrkl2yeByI+QEBWdxWIhMTERrbb435GhoaGonVh2UghPkadXBVNYF7CtDMyuCztYcOolAJpHNmdJ7yXcFnFb2TayOCc3w4rBkJoAPn7Q7QNo9nSpdvkWxF4M2pS/GLRkAIW4eaSlpfHRz3/jHxRa5H6ZaSmM6t6csDDXViASoixJAFjBBOqst9RgsmAwWdD5qFEUhT/O/wn4czH1LFpfLW+1f4sxbcd4V9bPYobN02HzNECBqo2sXb7hDT3SHHsx6AK7gG1jAL3o+yeEKDV+gUEEBId6uhlCuI1X5KnnzJlD7dq18fX1pU2bNuzatavQfefPn88999xDpUqVqFSpEh07dixy/5tNgD6nXElalomLKRfptbwXy/Zb1/AN8wthz5A9jG833ruCv5R4+G8v2DwVUKD5MzD4N48FfwB6H+v3suBJIFIGRgghRPnl8QDwq6++YtSoUUyYMIG//vqL22+/nc6dO3Pp0qUC99+0aRNPPvkkGzduZMeOHdSoUYNOnTpx4cKFMm65d/LRqO017P6772uafNqEn/79CY3KOqu3d8PuxETEeLKJ+ahOboTP2sLpraANgIfmQa85oPP3aLt0PrYu4MIzgBIACiGEKI88HgDOnDmTwYMHM2DAABo3bszcuXPx9/dn0aJFBe6/dOlSXnzxRZo1a0bDhg1ZsGABFouFDRs2lHHLvZefznpbR/86nqTMJFpFt+L5li8CoPPxooDFYqLRxW/QfPkYpF+BiKbw/Ga4/XFPtwzIKQZ9Yxew2aKQkiUrgQghhCi/PBoNGAwG9uzZw7hx4+yvqdVqOnbsyI4dOxw6R3p6OkajsdBBt1lZWWRlZdm3U1JSADAajRiNxhK03vsoisL//vkfVzNVaIhApw5mQod3GXXnKGatPwVcR61SvONzJ19E/f1gbk3YCYC5eT8sD7wLWj/whvYB2uyi2elZhjzfM1v3L4CvBu/4frqB7XNUlM9Tnsm98B62e2A2K1gs+SeE5aYoZvuzxWg0oihmh4+x/dvd1/DGNrl6DZOpbCcCVnQeDQCvXLmC2WwmIiIiz+sREREcOXLEoXOMGTOG6OhoOnbsWOD7U6ZM4e233873+pYtWzh06JDzjfZSVwxX+PTcp/yV8hdRymw0wPPRI2iaVIVf1/7Kv6fVgJpzZ06zZs1Jj7Y1/PrftDjzOVpzKka1L/tqDuQid8K6jR5t142uJ1q/Z3v2/o3u4j7764lZAD5oVQobfl3rodaVnnXr1nm6CSKb3Avvcfr0aXwDrha5T2ZaCusyTxAUFERKSgonLqjxDQhy6BjAqf0dvYY3tsnVa+y4eKXIfYRzvKg/0HlTp05l+fLlbNq0CV9f3wL3GTduHKNGjbJvX7hwgcaNG9OuXTtq165dRi0tPYqi8MX+L3h1/askZyWj1+ipGRpB/DVo36oTXZpGArB79RGIO0uDenXp+kB9zzTWbES96T00Jz8BwBIRw+bKz3JX92do5kB9rbL2c/LfHLiWwK2NmtD1zpr21w/HpcBfOwgJ0NO1awfPNdDNjEYj69at44EHHnCo3pkoPXIvvIfRaGTFihXUrl2boNBKRe6bnpLEA/fcQlhYGImJiZzaerLY0jG2YwCn9nf0Gt7YJlevEVvLQ8+uCsqjAWCVKlXQaDQkJCTkeT0hIYHIyMgij/3ggw+YOnUq69ev57bbCq9jp9fr0ev19u3k5GQAtFptuf/Feu76OQb/NJhfTvwCQJtqbVjcazHTVqUQf+0ymWbsn9FiLQOITuvjmc+ddM66nNv57BnbrYdgvncCab9u8Np74ZddUsesqPK0L8Nk/WYG+3lnu0vKW+/HzUjuhffQaFSo1Zoi91GpNPZ7ptVqUak0Dh9j+7e7r+GNbXL1Gj7eNIa9AvDoJBCdTkfLli3zTOCwTeiIjY0t9Ljp06fzzjvvsHbtWlq1alUWTfUqiqKw4K8FNPm0Cb+c+AW9Rs/0jtPZPnA7jao2ylkOLlcxaFshaNvM1jJ1ZA3Mvdsa/OlD4LH/Qtf3wUdf/LEepPcpuBB0sn0GsDyYhRBClE8eD6dHjRpFv379aNWqFa1bt2bWrFmkpaUxYMAAAJ599lmqVavGlClTAJg2bRpvvfUWy5Yto3bt2sTHxwMQGBhIYGDZLRPmKWevn+W5H59j3Unr2KA7q9/J4l6LaVglp16erRh07gDQvhScugwH0ZoMsH4C/PGpdTu6BTy6GCrVLrs2lEBhZWBsq4AESwkYIYQQ5ZTHn2CPP/44ly9f5q233iI+Pp5mzZqxdu1a+8SQs2fP5llX8bPPPsNgMPDII4/kOc+ECROYOHFiWTa9TCmKwvy/5vPqr6+SYkjB18eXd+99l5fvfBnNDanznOXgcjJXxuw+YK2mjDKA107DNwPg4l/W7TuHQceJ4KMrm+u7QWFlYGQVECGEEOWdxwNAgOHDhzN8+PAC39u0aVOe7dOnT5d+g7zMmaQzPPfTc6w/uR6Au2rcxaKei2hQpUGB+wdmrwaStwvYGsRoNWWQATz0A/zwH8i6Dr6h0PszaNi19K/rZoVlAGUVECGEEOWdPMG8mEWxMG/PPEavG02qIRVfH18m3zeZl9q8lC/rl1tBYwDtXcClmQE0ZsKv4+HP+dbt6q3hkUUQWqP0rlmKClsKTopACyGEKO8kAPRSp66d4rmfnuO3U78B0LZGWxb3Wkz9ysVPg8/pAs4dAJZyF/DVE/BNf4jfb91uOwLuexO8ab1hJ+kKmwRiywDq5cdHCCFE+SRPMC9jUSzM3T2X19a9RpoxDT8fP6bcP4XhrYcXmfXLLdCWATTkzwCWShfwP9/CTy+DIQX8wuChz+HWTu6/ThkrbgygdAELIYQor+QJ5kVOXjvJoB8Hsen0JgDuqXkPi3otol5YPafOU9AkEFsZGB+1GzOAxgxYOxb2LLFu17wLHl4AIdXcdw0PKnQMoG0WsHQBCyGEKKckAPQCFsXCp39+ypj1Y0g3puOv9Wfq/VMZ1noYapXzAVtAAZNAjBY3ZwCvHLN2+SYcAFRwzyvQYRxoKs7/UoWNAZQ6gEIIIcq7ivO0LqdOJJ5g0I+D2HxmMwDta7VnYc+F1A2r6/I5A4uYBOKWMYB/fwWrRoIxDQKqQp95UPe+kp/Xy+R0AecdAyh1AIUQQpR38gTzEIti4ZNdnzBuwzjSjekEaAOY1nEaL9zxgktZv9wKmgRicsckEEM6rBkN+/7Pul37HmuXb1DRy/aVV4WXgZEMoBBCiPJNAkAPOJ54nIE/DGTr2a0AdKjdgYU9F3JLpVvccv7cGUBFUVCpVLnKwLjYBXzpsLXL9/IRQAUdxkK70eDgxJTyqPBJIFIHUAghRPkmT7AyZFEszN45m9c3vE6GKYMAbQDvP/A+z7d6vsRZv9xsAaBFgUyjBT+dJlcZGCcDQEWBfUth9atgyoDACGvWr047t7XXWxWUAcwyme3bMglECCFEeSUBYBk5dvUYA38cyLaz2wC4r859LOy5kNqhtd1+LX+dBpXKGrulZpnw02lyrQTiRKCZlQqrR8H+r6zbt9wLfeZDYFW3t9kb2SaB5M4A2krAQE6gLYQQQpQ38gQrZWaL2Zr1++11Mk2ZBOoC+eCBDxjScggqVeksy6ZSqQjQ+ZCaZSIty0TVIL19LWCHy8DEH7B2+V49Bio13PsG3D0K3FlGxsvpCygEba8BqPdBoy6DZfWEEEKIUiABYCn69+q/DPhhAL+f+x2Ajrd0ZEGPBdQKrVXq1w7Qa0jNMtkngjhcCFpRrHX9fh4D5iwIioZHFkKtu0q5xd5HX0AXsKwDLIQQoiKQp1gpMFvMzPpjFuM3jifTlEmQLogZnWbwXIvnSi3rdyPrTOAseykYh2YBZybDqpfhwHfW7XoPWFf1CKhcuo31UkV1Acv4PyHKL4vFQlJSkkP7BgQElG5jhPCQm6c/r4wcuXKEuxffzavrXiXTlEmnup048OIBBrccXGbBH+RfDs5Q3CzguL9hXntr8KfSwAOT4Kmvb9rgDwqeBJIsM4CFKPeSkpKYuWovn248XuTXzFV7HQ4UhfeZMmUKd9xxB0FBQYSHh9O7d2+OHj2aZ58OHTqgUqnyfA0dOjTPPmfPnqVbt274+/sTHh7O6NGjMZlMefbZtGkTLVq0QK/XU69ePZYsWVLaH6/E5CnmJmaLmZk7ZvLmxjfJMmcRrA9mZqeZDGw+sEwDP5sAXd7l4AqdBKIo8OcC+OV1MBsgpAY8sghqtC7T9nojWxew2aJgMlvw0ahzlYCRDKAQ5ZlvQBABwaGeboYoRZs3b2bYsGHccccdmEwmXn/9dTp16sShQ4fyZHYHDx7MpEmT7Nv+/v72f5vNZrp160ZkZCS///47cXFxPPvss2i1WiZPngzAqVOn6NatG0OHDmXp0qVs2LCB5557jqioKDp37lx2H9hJEgC6weHLhxnwwwB2XtgJwIP1HmRe93nUCKnhsTYF5KoFaLYoZM8ByRsAZiTBj/+Bwz9atxt0hV5zwD+sbBvrpWwZQLBmUK0BYHYXsGQAhRDCq61duzbP9pIlSwgPD2fPnj20a5dTyszf35/IyIIXNPj11185dOgQ69evJyIigmbNmvHOO+8wZswYJk6ciE6nY+7cudSpU4cZM2YA0KhRI7Zt28aHH37o1QGgdAGXgMliYvr26TT/vDk7L+wkWB/Mop6LWPPUGo8GfwCBudYDtk0AgVxdwBf2wOftrMGfWgudp8ATyyT4y0WfOwDM7gbOmQQiGUAhhPCElJQUkpOT7V9ZWVkOHXf9+nUAwsLyPueWLl1KlSpVaNq0KePGjSM9Pd3+3o4dO4iJiSEiIsL+WufOnUlOTubgwYP2fTp27JjnnJ07d2bHjh0ufb6yImkMFx26fIgBPwxg14VdAHSp14V5PeZRPbi6h1tmlXs5OJMt/Qfo1CrY8SmsewssRgitBY8uhmotPdVUr+WjUaNWWQtq28YBJtsngciPjhBCeELjxo3zbE+YMIGJEycWeYzFYuHll1+mbdu2NG3a1P76U089Ra1atYiOjmb//v2MGTOGo0ePsmLFCgDi4+PzBH+AfTs+Pr7IfZKTk8nIyMDPz8+lz1na5CnmJJPFxAe/f8CETRMwmA2E6EOY9eAs+t3ezyNj/QqTezk42/i/EFLRffsM/PuzdadGPaHnx+AX6qFWej+9j4YMo5ksoy0AlAygEEJ40qFDh6hWrZp9W6/XF3vMsGHDOHDgANu2bcvz+pAhQ+z/jomJISoqivvvv58TJ05Qt25d9zXaC0kA6ISDlw7S/4f+7L64G4Cu9bsyr/s8qgVXK+bIspeTATRjMFtoofqX2bpPUP97BTQ66DwZ7ngOvCho9UZ6rZoMoxmD2TqZxl4IWsYACiGERwQFBREcHOzw/sOHD2fVqlVs2bKF6tWL7qVr06YNAMePH6du3bpERkaya9euPPskJCQA2McNRkZG2l/LvU9wcLDXZv9AxgA6xGQxMXnrZFrMa8Hui7sJ9Q3li95fsOrJVV4Z/EGuSSCZBvQ7P+Er3TtUV12BSnVg0DpoPViCPwfosifNZBrzjgEMlgygEEJ4NUVRGD58ON9//z2//fYbderUKfaYffv2ARAVFQVAbGws//zzD5cuXbLvs27dOoKDg+1d0bGxsWzYsCHPedatW0dsbKybPknpkDRGMf5J+IcBPwxgT9weALrf2p3Pu39OdFC0h1tWtEC9hkokM+jcLEL+3QUqWKPE0vX5r8HX8b+cbnZ6rTUAtNVRlAygEEKUD8OGDWPZsmX88MMPBAUF2cfshYSE4Ofnx4kTJ1i2bBldu3alcuXK7N+/n5EjR9KuXTtuu+02ADp16kTjxo3p27cv06dPJz4+nvHjxzNs2DB71/PQoUP55JNPeO211xg4cCC//fYbX3/9NatXr/bYZ3eEPMUKYTQbmbZ9GpM2T8JoMVLJtxKzu8zm6ZinvWqsX2FqpOxjjf51ojISsWj0vJH5DKu1negqwZ9TbBlA2xjAlKzsDKCsBCKEEF7ts88+A6zFnnNbvHgx/fv3R6fTsX79embNmkVaWho1atTg4YcfZvz48fZ9NRoNq1at4oUXXiA2NpaAgAD69euXp25gnTp1WL16NSNHjuSjjz6ievXqLFiwwKtLwIAEgAXan7Cf/iv7szd+LwA9G/Rkbre5RAVFebhlDrBYYNtM7tw6GbXKzDl1dUx9FvHl/65QxU/j6daVO/bl4My2LmCpAyiEEOWBoihFvl+jRg02b95c7Hlq1arFmjVritynQ4cO7N2716n2eZo8xXIxmo1M2TaFd7e8i9FiJMwvjI+7fMyTTZ8sF1k/Ui/DisFwciNqYIX5bub7D2N6SENgGz5qGfLpLPtycEYziqLISiBCCCEqBAkAs/0d/zf9f+jPvvh9APRu2JvPun1GZGDB1cG9zqkt8N1zkJoAPn5caPsOo36JoopBh9GSvQycTzkIYr2MPtd6wGkGs31FFZkEIoQQojy76QNAg9nAlK1TeHfru5gsJsL8wvikyyc80fSJ8pH1s5hhy/uweRooFqjaEB5dgllTC37ZmF0H0Bq1aCUD6DS9NrsL2GSxZ/981Cp8tfK9FMJbWCwWkpKSit0vNDQUtfweFAK4yQPAv+P/pt/Kfvyd8DcAfRr14dOunxIRGFHMkV4iJd7a5Xtqi3W72TPQdTroAghItS6Nk2E0k2Wy1rCzLwMnHGafBGKy5KwD7KctH38cCHGTSEpKYuaqvfgGBBW6T2ZaCqO6N8+3DJgQN6ubOgC8kn6FvxP+prJfZeZ0ncNjTR4rPw/2E7/BiiGQdhm0AdB9Jtz+hP1tWx1AgKR0a+ZKq5G/fJ1lLwNjMudaB/im/rERwiv5BgQREBzq6WYIUW7c1E+y+2+5n/k95tOzQU/CA8I93RzHmE2waQpsnQEoEN4EHl0CVW/Ns5veR42PWoXJopCUHbj4SADoNH1BGUAZ/yeEEKKcu6kDQIDnWjzn6SY47voF60SPs79bt1sOgAengDb/UjMqlYoAvQ/XM4xcTzcAoFWXk+ymF8nJAFpyrQN80//YCCGEKOfkSVZeHFtn7fLNSARdEPSYBTGPFHlIYHYAeE26gF2WewxgsqwCIoQQooKQJ5m3Mxvht3dg+0fW7cjbrF2+lesWe2iA3jqD1TYGUCaBOM82CzjLZLbPApYuYCGEEOWdBIDeLOkcfDsQzu+ybt8xGDq9C1pfhw63TQS5nmHtAtZJBtBptjqABpPFvgqIFIEWQghR3kkA6K2OrIGVL0BmEuhDoNfH0LiXU6cIzA4Ar0kG0GW5u4BNFts6wK7/2JjNZoxGo1va5m5GoxEfHx8yMzMxm82ebs5NzdvvhUajwcfHp/xUTRBC5CMBoLcxGWD9RPhjjnU7ugU8sgjC6jh9qgCd9fYmZU8CkVnAzss9CcSYvQyIqxnA1NRUzp8/X+z6lJ6iKAqRkZGcO3dOHuweVh7uhb+/P1FRUeh0Ok83RQjhAgkAvcm109Yu3wt7rNt3vggd3wYf137B2rqAbWMApQvYebkzgGkG1yeBmM1mzp8/j7+/P1WrVvXKh7rFYiE1NZXAwEBZLcHDvPleKIqCwWDg8uXLnDp1ivr163tdG4UQxZMA0Fsc+hF+GA5Z18E3FHp/Bg27luiUgbZJIBk5S5gJ5+RMArHYC0G7MgnEaDSiKApVq1bFzy9/2R5vYLFYMBgM+Pr6ygPdw7z9Xvj5+aHVajlz5oy9nUKI8kUCQE8zZcGv42HXPOt29TusXb6hNUt86sDsTJU5u+tSuoCdl5MBNOcqBO36j403Zv6EcEVpBaaOrusLsravECUhAaAnXT0B3w6AOOtaxLQdAfe9CRr3zDLNvRwcgE4mgTjNNgbwxrWAhRClw5F1fUHW9hWipCQA9JQD38GPI8CQAn5h8NDncGsnt14i8IYAUDKAztP7WLuAZSUQIcqOrOsrROmTJ1lZM2bA2nGwZ7F1u2YsPLwQQqq5/VK2WcA2shKI83TZdQDTDSbSDdZyHO6qA+hMV5e7lLcus9OnT1OnTh327t1Ls2bNPN0cAI4cOUL//v3Zt28fDRs2ZN++fWV27YkTJ7Jy5coyvaYQomKSALAsXTkG3/SHhAOACu4ZBR1eB03p3IYbu4C10gXsNFsh6KupBvtr7soAOtrV5S6udJn179+fL774gilTpjB27Fj76ytXruShhx7y2pI2pWnChAkEBARw9OhRAgMDy/Tar776Kv/5z3/K9JpCiIpJAsCy8vdXsGokGNPAvwr0mQf17i/VS+brAi5HmR9vYcsAJmbXUvTTatyaSS0PXV2+vr5MmzaN559/nkqVKnm6OW5hMBhcrl934sQJunXrRq1atcrkerkFBgaWedAphKiYJCIobYZ0+GEYfD/EGvzVvgde2F7qwR/krAVso/WRDKCzbBlAW6KrJKuAlFcdO3YkMjKSKVOmFLrPxIkT83XRzpo1i9q1a9u3+/fvT+/evZk8eTIRERGEhoYyadIkTCYTo0ePJiwsjOrVq7N48eJ85z9y5Ah33XUXvr6+NG3alM2bN+d5/8CBA3Tp0oXAwEAiIiLo27cvV65csb/foUMHhg8fzssvv0yVKlXo3LlzgZ/DYrEwadIkqlevjl6vp1mzZqxdu9b+vkqlYs+ePUyaNAmVSsXEiRMLPE9h1yuqnfPmzSM6OhqLxZLnXL169WLgwIGFfp8XLFhAo0aN8PX1pWHDhnz66af29x555BGGDx9u33755ZdRqVQcOXIEsAamAQEBrF+/HoBvv/2WmJgY/Pz8qFy5Mh07diQtLa3AzyiEKN8kACxNl47A/Ptg7/8BKmg/Fp79AYIiy+TyN2YAtZIBdJotALS5GdcB1mg0TJ48mY8//pjz58+X6Fy//fYbFy9eZMuWLcycOZMJEybQvXt3KlWqxM6dOxk6dCjPP/98vuuMHj2aV155hb179xIbG0uPHj24evUqYO1Kv++++2jevDm7d+9m7dq1JCQk8Nhjj+U5xxdffIFOp2P79u3MnTu3wPZ99NFHzJgxgw8++ID9+/fTuXNnevbsybFjxwCIi4ujSZMmvPLKK8TFxfHqq68W+llvvF5x7Xz00Ue5evUqGzdutJ8jMTGRtWvX8vTTTxd4jaVLl/LWW2/x3nvvcfjwYSZPnsybb77JF198AUD79u3ZtGmTff/NmzdTpUoV+2t//vknRqORu+66i7i4OJ588kkGDhzI4cOH2bRpE3369Lkpu/mFuBlIRFAaFMUa9M3rAJcPQ2CENfC7dxyoNcUe7i43jgGUtYCdZ5sFbFOSGoDl2UMPPUSzZs2YMGFCic4TFhbG7NmzadCgAQMHDqRBgwakp6fz+uuvU79+fcaNG4dOp2Pbtm15jhs+fDgPP/wwjRo14rPPPiMkJISFCxcC8Mknn9C8eXMmT55Mw4YNad68OYsWLWLjxo38+++/9nPUr1+f6dOn06BBAxo0aFBg+z744APGjBnDE088QYMGDZg2bRrNmjVj1qxZAERGRuLj40NgYCCRkZFFdsfeeL3i2lmpUiW6dOnCsmXL7Of49ttvqVKlCvfee2+B15gwYQIzZsygT58+1KlThz59+jBy5Eg+//xzwJqJPHToEJcvX+batWscOnSIESNG2APATZs2cccdd+Dv709cXBwmk4k+ffpQu3ZtYmJiePHFF6XLWYgKSgJAd8tKhe+HWrt9TRlwSwcYug1uaV/mTck/CURut7MkA5hj2rRpfPHFFxw+fNjlczRp0iTPLOSIiAhiYmLs2xqNhsqVK3Pp0qU8x8XGxtr/7ePjQ6tWrezt+Pvvv9m4caN9fFxgYCANGzYErOP1bFq2bFlk25KTk7l48SJt27bN83rbtm1d+sw3Xs+Rdj799NN89913ZGVlAfDll1/yxBNPFDhzOy0tjRMnTjBo0KA853z33Xft52vatClhYWFs3ryZrVu30rx5c7p3727vQt+8eTMdOnQA4Pbbb+f+++8nJiaGRx99lPnz53Pt2jWnP7cQony4OdMZpSX+gLWw85V/QaWGe1+Hu18BD3W9BuhuGAMoGUCn6fIFgDfvj0y7du3o3Lkz48aNo3///nneU6vV+boKjUZjvnNotXkDaJVKVeBrN46DK0pqaio9evRg2rRp+d6Lioqy/zsgIMDhc7rDjddzpJ09evRAURRWr15Nw4YN2bp1Kx9++GGB509NTQVg/vz5tGnTJs97Go31Z1+lUtGuXTs2bdqEXq+nQ4cO3HbbbWRlZXHgwAF+//13eze2RqNh3bp1/P777/z66698/PHHvPHGG+zcuZM6deqU7JshhPA6N+/TzJ0UBfYsgbVjwZQJQVHW2n612xZ7aGny0ajx1arJNFofppIBdF6+LuCbfBWQqVOn0qxZs3xdqFWrViU+Ph5FUezL3bmzVt0ff/xBu3btADCZTOzZs8c+uaFFixZ899131K5dGx8f13+lBQcHEx0dzfbt22nfPidjv337dlq3bl2yD+BgO319fenTpw/Lli3j9ttvp0GDBrRo0aLAfSMiIoiOjubkyZOFjhEE6zjA+fPno9free+991Cr1bRr147333+frKysPBlPlUpF27Ztadu2LW+99Ra1atXi+++/Z9SoUS5/bmeXdhNClA0JAEsqMxlWvWxd2QOg3gPw0FwIqOLRZtkE6n3INFpLmMhKIM4r7QxgZlqKW89X2teKiYnh6aefZvbs2Xle79ChA5cvX2b69Ok88sgjrF27lp9//png4OASXxNgzpw51K9fn0aNGvHhhx9y7do1+8zYYcOGMX/+fJ588klee+01wsLCOH78OMuXL2fBggX2bJgjRo8ezYQJE6hbty7NmjVj8eLF7Nu3j6VLl5b4Mzjazqeffpru3btz4MAB+vbtW+Q53377bV566SVCQkJ48MEHycrKYvfu3Vy7ds0etHXo0IGRI0ei0+m4++677a+9+uqr3HHHHfZM5c6dO9mwYQOdOnUiPDycnTt3cvnyZRo1alSiz+3s0m5CiLIhAWBJxP1tLeyceBJUGrj/LbjrJY91+RYkQO/Dlewixlq1dAE7S6NW4aNWYbJYuzeD3TgGMDQ0tMwfeO7IsEyaNImvvvoqz2uNGjXi008/ZfLkybzzzjs8/PDDvPrqq8ybN6/E1wNr5nHq1Kns27ePevXq8eOPP1KlivWPLFvWbsyYMXTq1ImsrCxq1arFgw8+6PSqJy+99BLXr1/nlVde4dKlSzRu3Jgff/yR+vXrl/gzONrO++67j7CwMI4dO8aTTz5Z5Dmfe+45/P39ef/99xk9ejQBAQHExMTw8ssv2/eJiYkhNDSUW2+91T6ho0OHDpjNZvv4P7BmQLds2cKsWbNITk6mVq1azJgxgy5dupT4s5eHepdC3GwkAHSFosCfC+CX18FsgODq8MgiqNmm+GPLWO7l4KQL2DU6HzWm7GXg3DkLWK1We/1C9kuWLMn3Wu3ate2TFHIbOnQoQ4cOzfPa66+/XuS5cpcosTl9+nSea9nGFhYVDNWvX58VK1YU+n5B1ymIWq1mwoQJRc52dqRru7DrFddOWxvOnz9PcnJyvgzqxIkT89UefOqpp3jqqaeKPF9iYmKe15o1a5ZvzGajRo3y1DwUQlRsEgA6K/M6/PgfOPSDdfvWLtD7U/D3zgd57lqAUgbGNXoftdvXARZCCCE8SQJAZ1zYA98MgKQzoNbCA2/DnS+CynsDq9yrgUgG0DXWiSDWGa0340ogQgghKh55mjlCUWDnXPj1TbAYIbQmPLIEqhddV8wb5K4FKAGga3JPBJEMoLiZKYqC2WzNhptMJvsM34LWOQ4NDXV6DKYQouxIAFic9ET4YTgcXW3dbtQDen4CfqEebZajpAu45HIXg3bnJBAhyhuz2UxCUjoqjQaTwUBKppFfd50l7YaSj7YZvd4+xlWIm5kEgEU596e1sPP1c6DRQaf3oPVgr+7yvVHuDKBOMoAuyZsBLNmPjKyrKrxJ7oxecezFpTUaNBoNFrUalUqNX0AwWOR3ixDljQSABbFYYMfHsGESWExQqQ48ugSim3m6ZU4LkAxgieXJALpYCNr28DQYDPj5+bmlXUKUVO6MXlEUs5mIUP88rxmyMjErCgaL/F4RojySAPBGaVdh5Qtw7BfrdpM+0OMj8HVPQduyFphrEoiPjMdxiS0DqFblX17PUT4+Pvj7+3P58mW0Wq1Xjo2yWCwYDAYyMzO9sn03E1fvhaMZPY1Gg0qlwmQyYTabUFN0ZtpiNpOZmQmA0ZBFptHI1SuXuZiuxowEgEKURxIA5nZmB3w7EFIugkYPXaZCywHlqsv3RtIFXHK25eAC9T72Zc6cpVKpiIqK4tSpU5w5c8adzXMbRVHIyMjAz8/P5c8p3MN2L/R6vUP3QqVS2ddQTk43oCqi6LtiUQj216FWq7FYLKRkGlGpiv7doCgWUrLHvyZnGFFUKi6mqzmXmX/yhxCifJAAEKxdvts/hN/eA8UMletZu3wjYzzdshKTSSAlZ+sCLuk6wDqdjvr162MwGNzRLLczGo1s2bKFdu3aodXKZBdPMhqN/Pzzz5wwh+EbUHTvQ1Z6Gv07NCI0NJSkpCR+PXEWvyKWXctIS+HJ1lE5++8qev+cYyIB+GXnWXz8QyTzJ0Q5JwFg6mX4fgic+M26fdvj0G0m6AM92y43yb0SiASArrF1AbujBIxarcbX17fE5ykNGo0Gk8mEr6+vBIClwFYyxREBAQEYDAZMvgHFVhwwGa1/XPj6+qLT6awzci2FD1VIc3L/3McApJsgQII/Ico9rwgA58yZw/vvv098fDy33347H3/8Ma1bty50/2+++YY333yT06dPU79+faZNm0bXrl2dv/CprfDdc5AaDz5+0PV9aP5Mue7yvZF0AZecrQvYncvAifLNmWDOVg8vKSmJmav24ltMti0zLYX/dG7qhlYKIcD5GONm4fEn2ldffcWoUaOYO3cubdq0YdasWXTu3JmjR48SHh6eb//ff/+dJ598kilTptC9e3eWLVtG7969+euvv2ja1PFfmqqdn8GReaBYoEoDeOwLCG/kzo/mFfJ2AUsA6Ap3ZgCFd3I2oHMmmMtdD883IIiA4NAStlYI4ShnY4ybiccDwJkzZzJ48GAGDBgAwNy5c1m9ejWLFi1i7Nix+fb/6KOPePDBBxk9ejQA77zzDuvWreOTTz5h7ty5Dl9Xs/NTCFZDs2eg63TQBbjnA3mZvEvBVZzMZlmyjwG8CTKAFouFxMREh7qAQ0NDAZzOhDkbbJXmNVzJzo3q3hyQYE6I8sDZGONm4tEnmsFgYM+ePYwbN87+mlqtpmPHjuzYsaPAY3bs2MGoUaPyvNa5c2dWrlxZ4P5ZWVlkZWXZt69fvw7AxXQfrtw5BqVWZzj4b6FtrFSpkv3f165dK/Yz5T7G2f1L4xpJ6QayLp9B6xvAhbNnUatVDl2jLD53YGAgV65c4fTp06SmppbKNZz9HAXtn3T+DFmXL5KekMXevfnLZXjT/Xb1GpUqVcJoNHLu3DneWPATvgFFj4E1ZKbzQmdrIPTZL3vR+fo7tH+lSpW4du2aU8eU1jVu3P/6tat5flcUJDM91T6LO+H8aXz9i/4+WffXkpyczLVr1xw+5uxZFYmJicSZfAgIKvr+OXsNV9t05oz1j4LS/NyleQ1vvBe5jwHv+tzeeL8v6K0/z9evXyc4OGdylF6vR6/X5zvGlRjjpqJ40IULFxRA+f333/O8Pnr0aKV169YFHqPVapVly5bleW3OnDlKeHh4gftPmDBBAeRLvuRLvuRLvuSrAn5NmDDBbTHGzaTC92mNGzcuT8YwMTGROnXqcODAAUJCQjzYMpGSkkLjxo05dOgQQUFFd72J0if3w3vIvfAeci+8x/Xr12natCmnTp3Ks850Qdk/UTyPBoBVqlRBo9GQkJCQ5/WEhAQiIyMLPCYyMtKp/QtLDdeoUSNPClmUveTkZACqVasm98ILyP3wHnIvvIfcC+9h+/6HhYU5dC9ciTFuJh6dFqrT6WjZsiUbNmywv2axWNiwYQOxsbEFHhMbG5tnf4B169YVur8QQgghbj6uxBg3E493AY8aNYp+/frRqlUrWrduzaxZs0hLS7PP2Hn22WepVq0aU6ZMAWDEiBG0b9+eGTNm0K1bN5YvX87u3buZN2+eJz+GEEIIIbxMcTHGzczjAeDjjz/O5cuXeeutt4iPj6dZs2asXbuWiIgIAM6ePZtnMfS77rqLZcuWMX78eF5//XXq16/PypUrHa4BqNfrmTBhgowZ8AJyL7yL3A/vIffCe8i98B6u3IviYoybmUpRFMXTjRBCCCGEEGVHloYQQgghhLjJSAAohBBCCHGTkQBQCCGEEOImIwGgEEIIIcRNpkIGgHPmzKF27dr4+vrSpk0bdu3aVeT+33zzDQ0bNsTX15eYmBjWrFlTRi2t+Jy5F/Pnz+eee+6hUqVKVKpUiY4dOxZ774RznP3ZsFm+fDkqlYrevXuXbgNvIs7ei6SkJIYNG0ZUVBR6vZ5bb71Vfle5ibP3YtasWTRo0AA/Pz9q1KjByJEjyczMLKPWVlxbtmyhR48eREdHo1KpWLlyZbHHbNq0iRYtWqDX66lXrx5Lliwp9XZWGJ5ei87dli9fruh0OmXRokXKwYMHlcGDByuhoaFKQkJCgftv375d0Wg0yvTp05VDhw4p48ePV7RarfLPP/+UccsrHmfvxVNPPaXMmTNH2bt3r3L48GGlf//+SkhIiHL+/PkybnnF5Oz9sDl16pRSrVo15Z577lF69epVNo2t4Jy9F1lZWUqrVq2Url27Ktu2jh98PwAADCdJREFUbVNOnTqlbNq0Sdm3b18Zt7zicfZeLF26VNHr9crSpUuVU6dOKb/88osSFRWljBw5soxbXvGsWbNGeeONN5QVK1YogPL9998Xuf/JkycVf39/ZdSoUcqhQ4eUjz/+WNFoNMratWvLpsHlXIULAFu3bq0MGzbMvm02m5Xo6GhlypQpBe7/2GOPKd26dcvzWps2bZTnn3++VNt5M3D2XtzIZDIpQUFByhdffFFaTbypuHI/TCaTctdddykLFixQ+vXrJwGgmzh7Lz777DPllltuUQwGQ1k18abh7L0YNmyYct999+V5bdSoUUrbtm1LtZ03G0cCwNdee01p0qRJntcef/xxpXPnzqXYsoqjQnUBGwwG9uzZQ8eOHe2vqdVqOnbsyI4dOwo8ZseOHXn2B+jcuXOh+wvHuHIvbpSeno7RaMyz6Ldwjav3Y9KkSYSHhzNo0KCyaOZNwZV78eOPPxIbG8uwYcOIiIigadOmTJ48GbPZXFbNrpBcuRd33XUXe/bssXcTnzx5kjVr1tC1a9cyabPIIc/vkvH4SiDudOXKFcxmc74K3xERERw5cqTAY+Lj4wvcPz4+vtTaeTNw5V7caMyYMURHR+f7ARfOc+V+bNu2jYULF7Jv374yaOHNw5V7cfLkSX777Teefvpp1qxZw/Hjx3nxxRcxGo1MmDChLJpdIblyL5566imuXLnC3XffjaIomEwmhg4dyuuvv14WTRa5FPb8Tk5OJiMjAz8/Pw+1rHyoUBlAUXFMnTqV5cuX8/333+Pr6+vp5tx0UlJS6Nu3L/Pnz6dKlSqebs5Nz2KxEB4ezrx582jZsiWPP/44b7zxBnPnzvV00246mzZtYvLkyXz66af89ddfrFixgtWrV/POO+94umlCOKVCZQCrVKmCRqMhISEhz+sJCQlERkYWeExkZKRT+wvHuHIvbD744AOmTp3K+vXrue2220qzmTcNZ+/HiRMnOH36ND169LC/ZrFYAPDx8eHo0aPUrVu3dBtdQbnysxEVFYVWq0Wj0dhfa9SoEfHx8RgMBnQ6Xam2uaJy5V68+eab9O3bl+eeew6AmJgY0tLSGDJkCG+88UaetetF6Srs+R0cHCzZPwdUqP9TdTodLVu2ZMOGDfbXLBYLGzZsIDY2tsBjYmNj8+wPsG7dukL3F45x5V4ATJ8+nXfeeYe1a9fSqlWrsmjqTcHZ+9GwYUP++ecf9u3bZ//q2bMn9957L/v27aNGjRpl2fwKxZWfjbZt23L8+HF7EA7w77//EhUVJcFfCbhyL9LT0/MFebbAXFGU0musyEee3yXk6Vko7rZ8+XJFr9crS5YsUQ4dOqQMGTJECQ0NVeLj4xVFUZS+ffsqY8eOte+/fft2xcfHR/nggw+Uw4cPKxMmTJAyMG7i7L2YOnWqotPplG+//VaJi4uzf6WkpHjqI1Qozt6PG8ksYPdx9l6cPXtWCQoKUoYPH64cPXpUWbVqlRIeHq68++67nvoIFYaz92LChAlKUFCQ8uWXXyonT55Ufv31V6Vu3brKY4895qmPUGGkpKQoe/fuVfbu3asAysyZM5W9e/cqZ86cURRFUcaOHav07dvXvr+tDMzo0aOVw4cPK3PmzJEyME6ocAGgoijKxx9/rNSsWVPR6XRK69atlT/++MP+Xvv27ZV+/frl2f/rr79Wbr31VkWn0ylNmjRRVq9eXcYtrricuRe1atVSgHxfEyZMKPuGV1DO/mzkJgGgezl7L37//XelTZs2il6vV2655RblvffeU0wmUxm3umJy5l4YjUZl4sSJSt26dRVfX1+lRo0ayosvvqhcu3at7BtewWzcuLHAZ4Dt+9+vXz+lffv2+Y5p1qyZotPplFtuuUVZvHhxmbe7vFIpiuSshRBCCCFuJhVqDKAQQgghhCieBIBCCCGEEDcZCQCFEEIIIW4yEgAKIYQQQtxkJAAUQgghhLjJSAAohBBCCHGTkQBQCCGEEOImIwGgEMLr9e/fn969e9u3O3TowMsvv1zm7di0aRMqlYqkpKQyv7YQQriTBIBCCJf0798flUqFSqVCp9NRr149Jk2ahMlkKvVrr1ixgnfeecehfcs6aKtdu7b9++Lv709MTAwLFiwok2sLIYSjJAAUQrjswQcfJC4ujmPHjvHKK68wceJE3n///QL3NRgMbrtuWFgYQUFBbjufu02aNIm4uDgOHDjAM888w+DBg/n555893SwhhLCTAFAI4TK9Xk9kZCS1atXihRdeoGPHjvz4449ATrfte++9R3R0NA0aNADg3LlzPPbYY4SGhhIWFkavXr04ffq0/Zxms5lRo0YRGhpK5cqVee2117hxxcobu4CzsrIYM2YMNWrUQK/XU69ePRYuXMjp06e59957AahUqRIqlYr+/fsDYLFYmDJlCnXq1MHPz4/bb7+db7/9Ns911qxZw6233oqfnx/33ntvnnYWJSgoiMjISG655RbGjBlDWFgY69atc+I7K4QQpUsCQCGE2/j5+eXJ9G3YsIGjR4+ybt06Vq1ahdFopHPnzgQFBbF161a2b99OYGAgDz74oP24GTNmsGTJEhYtWsS2bdtITEzk+++/L/K6zz77LF9++SWzZ8/m8OHDfP755wQGBlKjRg2+++47AI4ePUpcXBwfffQRAFOmTOG///0vc+fO5eDBg4wcOZJnnnmGzZs3A9ZAtU+fPvTo0YN9+/bx3HPPMXbsWKe+HxaLhe+++45r166h0+mcOlYIIUqVIoQQLujXr5/Sq1cvRVEUxWKxKOvWrVP0er3y6quv2t+PiIhQsrKy7Mf873//Uxo0aKBYLBb7a1lZWYqfn5/yyy+/KIqiKFFRUcr06dPt7xuNRqV69er2aymKorRv314ZMWKEoiiKcvToUQVQ1q1bV2A7N27cqADKtWvX7K9lZmYq/v7+yu+//55n30GDBilPPvmkoiiKMm7cOKVx48Z53h8zZky+c92oVq1aik6nUwICAhQfHx8FUMLCwpRjx44VeowQQpQ1H8+Gn0KI8mzVqlUEBgZiNBqxWCw89dRTTJw40f5+TExMnszX33//zfHjx/ON38vMzOTEiRNcv36duLg42rRpY3/Px8eHVq1a5esGttm3bx8ajYb27ds73O7jx4+Tnp7OAw88kOd1g8FA8+bNATh8+HCedgDExsY6dP7Ro0fTv39/4uLiGD16NC+++CL16tVzuH1CCFHaJAAUQrjs3nvv5bPPPkOn0xEdHY2PT95fKQEBAXm2U1NTadmyJUuXLs13rqpVq7rUBj8/P6ePSU1NBWD16tVUq1Ytz3t6vd6lduRWpUoV6tWrR7169fjmm2+IiYmhVatWNG7cuMTnFkIId5AxgEIIlwUEBFCvXj1q1qyZL/grSIsWLTh27Bjh4eH2AMn2FRISQkhICFFRUezcudN+jMlkYs+ePYWeMyYmBovFYh+7dyNbBtJsNttfa9y4MXq9nrNnz+ZrR40aNQBo1KgRu3btynOuP/74o9jPeKMaNWrw+OOPM27cOKePFUKI0iIBoBCizDz99NNUqVKFXr16sXXrVk6dOsWmTZt46aWXOH/+PAAjRoxg6tSprFy5kiNHjvDiiy8WWcOvdu3a9OvXj4EDB7Jy5Ur7Ob/++msAatWqhUqlYtWqVVy+fJnU1FSCgoJ49dVXGTlyJF988QUnTpzgr7/+4uOPP+aLL74AYOjQoRw7dozRo0dz9OhRli1bxpIlS1z63CNGjOCnn35i9+7dLh0vhBDuJgGgEKLM+Pv7s2XLFmrWrEmfPn1o1KgRgwYNIjMzk+DgYABeeeUV+vbtS79+/YiNjSUoKIiHHnqoyPN+9tlnPPLII7z44os0bNiQwYMHk5aWBkC1atV4++23GTt2LBEREQwfPhyAd955hzfffJMpU6bQqFEjHnzwQVavXk2dOnUAqFmzJt999x0rV67k9ttvZ+7cuUyePNmlz924cWM6derEW2+95dLxQgjhbiqlsJHVQgghhBCiQpIMoBBCCCHETUYCQCGEEEKIm4wEgEIIIYQQNxkJAIUQQgghbjISAAohhBBC3GQkABRCCCGEuMlIACiEEEIIcZORAFAIIYQQ4iYjAaAQQgghxE1GAkAhhBBCiJuMBIBCCCGEEDcZCQCFEEIIIW4y/w+28gq516UAXwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.2505\n",
      "RMSE: 0.0496\n",
      "[0.31184115 0.6315716 ]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.6836\n",
      "RMSE: 0.0958\n",
      "[-0.591881    1.54336149]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9270\n",
      "RMSE: 0.0210\n",
      "[0.04440071 0.96335881]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: -0.3218\n",
      "RMSE: 0.0380\n",
      "[0.47874595 0.51378045]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row3_col5, #T_34cec_row4_col5 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row3_col6 {\n",
       "  background-color: #9d9dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row3_col7, #T_34cec_row9_col2 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row4_col4, #T_34cec_row6_col5 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row4_col6, #T_34cec_row13_col3 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row4_col7 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col1, #T_34cec_row5_col2, #T_34cec_row6_col1 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col3, #T_34cec_row10_col1 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col4, #T_34cec_row7_col5 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col5 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col6, #T_34cec_row6_col2 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row5_col7 {\n",
       "  background-color: #ffc1c1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row6_col4, #T_34cec_row10_col4 {\n",
       "  background-color: #ff7575;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row6_col6 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col1 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col2, #T_34cec_row10_col2 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col3 {\n",
       "  background-color: #ffe9e9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col4 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col6 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row7_col7, #T_34cec_row8_col7 {\n",
       "  background-color: #ff1919;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row8_col1, #T_34cec_row12_col1 {\n",
       "  background-color: #c1c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row8_col3, #T_34cec_row10_col3 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row8_col5, #T_34cec_row9_col3, #T_34cec_row11_col3 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row9_col0 {\n",
       "  background-color: #a5a5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row9_col1 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row9_col7, #T_34cec_row11_col4 {\n",
       "  background-color: #ff5959;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row10_col5 {\n",
       "  background-color: #ffdddd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row10_col6, #T_34cec_row12_col3 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row10_col7 {\n",
       "  background-color: #ff0505;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row11_col1 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row11_col6 {\n",
       "  background-color: #9595ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row12_col2 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row12_col5 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_34cec_row13_col1 {\n",
       "  background-color: #9191ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row13_col2 {\n",
       "  background-color: #7d7dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_34cec_row14_col2 {\n",
       "  background-color: #a1a1ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_34cec\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_34cec_level0_col0\" class=\"col_heading level0 col0\" >2</th>\n",
       "      <th id=\"T_34cec_level0_col1\" class=\"col_heading level0 col1\" >3</th>\n",
       "      <th id=\"T_34cec_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
       "      <th id=\"T_34cec_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
       "      <th id=\"T_34cec_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
       "      <th id=\"T_34cec_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
       "      <th id=\"T_34cec_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
       "      <th id=\"T_34cec_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row0\" class=\"row_heading level0 row0\" >1.400000</th>\n",
       "      <td id=\"T_34cec_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_34cec_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_34cec_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_34cec_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_34cec_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_34cec_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_34cec_row0_col6\" class=\"data row0 col6\" >2.55%</td>\n",
       "      <td id=\"T_34cec_row0_col7\" class=\"data row0 col7\" >2.96%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row1\" class=\"row_heading level0 row1\" >1.960000</th>\n",
       "      <td id=\"T_34cec_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_34cec_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_34cec_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_34cec_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_34cec_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_34cec_row1_col5\" class=\"data row1 col5\" >3.30%</td>\n",
       "      <td id=\"T_34cec_row1_col6\" class=\"data row1 col6\" >-4.94%</td>\n",
       "      <td id=\"T_34cec_row1_col7\" class=\"data row1 col7\" >-0.02%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row2\" class=\"row_heading level0 row2\" >2.740000</th>\n",
       "      <td id=\"T_34cec_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_34cec_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_34cec_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_34cec_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_34cec_row2_col4\" class=\"data row2 col4\" >5.08%</td>\n",
       "      <td id=\"T_34cec_row2_col5\" class=\"data row2 col5\" >-1.65%</td>\n",
       "      <td id=\"T_34cec_row2_col6\" class=\"data row2 col6\" >0.04%</td>\n",
       "      <td id=\"T_34cec_row2_col7\" class=\"data row2 col7\" >-0.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row3\" class=\"row_heading level0 row3\" >3.840000</th>\n",
       "      <td id=\"T_34cec_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_34cec_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_34cec_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_34cec_row3_col3\" class=\"data row3 col3\" ></td>\n",
       "      <td id=\"T_34cec_row3_col4\" class=\"data row3 col4\" >-0.96%</td>\n",
       "      <td id=\"T_34cec_row3_col5\" class=\"data row3 col5\" >-1.87%</td>\n",
       "      <td id=\"T_34cec_row3_col6\" class=\"data row3 col6\" >-3.82%</td>\n",
       "      <td id=\"T_34cec_row3_col7\" class=\"data row3 col7\" >1.00%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row4\" class=\"row_heading level0 row4\" >5.380000</th>\n",
       "      <td id=\"T_34cec_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_34cec_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_34cec_row4_col2\" class=\"data row4 col2\" >-1.05%</td>\n",
       "      <td id=\"T_34cec_row4_col3\" class=\"data row4 col3\" ></td>\n",
       "      <td id=\"T_34cec_row4_col4\" class=\"data row4 col4\" >-0.32%</td>\n",
       "      <td id=\"T_34cec_row4_col5\" class=\"data row4 col5\" >-1.82%</td>\n",
       "      <td id=\"T_34cec_row4_col6\" class=\"data row4 col6\" >-2.91%</td>\n",
       "      <td id=\"T_34cec_row4_col7\" class=\"data row4 col7\" >0.23%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row5\" class=\"row_heading level0 row5\" >7.530000</th>\n",
       "      <td id=\"T_34cec_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_34cec_row5_col1\" class=\"data row5 col1\" >-1.44%</td>\n",
       "      <td id=\"T_34cec_row5_col2\" class=\"data row5 col2\" >-1.41%</td>\n",
       "      <td id=\"T_34cec_row5_col3\" class=\"data row5 col3\" >-2.97%</td>\n",
       "      <td id=\"T_34cec_row5_col4\" class=\"data row5 col4\" >0.65%</td>\n",
       "      <td id=\"T_34cec_row5_col5\" class=\"data row5 col5\" >-0.60%</td>\n",
       "      <td id=\"T_34cec_row5_col6\" class=\"data row5 col6\" >-2.16%</td>\n",
       "      <td id=\"T_34cec_row5_col7\" class=\"data row5 col7\" >2.41%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row6\" class=\"row_heading level0 row6\" >10.540000</th>\n",
       "      <td id=\"T_34cec_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_34cec_row6_col1\" class=\"data row6 col1\" >-1.44%</td>\n",
       "      <td id=\"T_34cec_row6_col2\" class=\"data row6 col2\" >-2.14%</td>\n",
       "      <td id=\"T_34cec_row6_col3\" class=\"data row6 col3\" ></td>\n",
       "      <td id=\"T_34cec_row6_col4\" class=\"data row6 col4\" >5.40%</td>\n",
       "      <td id=\"T_34cec_row6_col5\" class=\"data row6 col5\" >-0.41%</td>\n",
       "      <td id=\"T_34cec_row6_col6\" class=\"data row6 col6\" >1.72%</td>\n",
       "      <td id=\"T_34cec_row6_col7\" class=\"data row6 col7\" >5.03%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row7\" class=\"row_heading level0 row7\" >14.760000</th>\n",
       "      <td id=\"T_34cec_row7_col0\" class=\"data row7 col0\" ></td>\n",
       "      <td id=\"T_34cec_row7_col1\" class=\"data row7 col1\" >-1.88%</td>\n",
       "      <td id=\"T_34cec_row7_col2\" class=\"data row7 col2\" >-0.89%</td>\n",
       "      <td id=\"T_34cec_row7_col3\" class=\"data row7 col3\" >0.90%</td>\n",
       "      <td id=\"T_34cec_row7_col4\" class=\"data row7 col4\" >3.55%</td>\n",
       "      <td id=\"T_34cec_row7_col5\" class=\"data row7 col5\" >0.78%</td>\n",
       "      <td id=\"T_34cec_row7_col6\" class=\"data row7 col6\" >1.93%</td>\n",
       "      <td id=\"T_34cec_row7_col7\" class=\"data row7 col7\" >9.06%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row8\" class=\"row_heading level0 row8\" >20.660000</th>\n",
       "      <td id=\"T_34cec_row8_col0\" class=\"data row8 col0\" ></td>\n",
       "      <td id=\"T_34cec_row8_col1\" class=\"data row8 col1\" >-2.49%</td>\n",
       "      <td id=\"T_34cec_row8_col2\" class=\"data row8 col2\" >-1.71%</td>\n",
       "      <td id=\"T_34cec_row8_col3\" class=\"data row8 col3\" >0.57%</td>\n",
       "      <td id=\"T_34cec_row8_col4\" class=\"data row8 col4\" >-0.04%</td>\n",
       "      <td id=\"T_34cec_row8_col5\" class=\"data row8 col5\" >2.13%</td>\n",
       "      <td id=\"T_34cec_row8_col6\" class=\"data row8 col6\" >2.90%</td>\n",
       "      <td id=\"T_34cec_row8_col7\" class=\"data row8 col7\" >8.97%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row9\" class=\"row_heading level0 row9\" >28.930000</th>\n",
       "      <td id=\"T_34cec_row9_col0\" class=\"data row9 col0\" >-3.54%</td>\n",
       "      <td id=\"T_34cec_row9_col1\" class=\"data row9 col1\" >-2.29%</td>\n",
       "      <td id=\"T_34cec_row9_col2\" class=\"data row9 col2\" >1.00%</td>\n",
       "      <td id=\"T_34cec_row9_col3\" class=\"data row9 col3\" >2.11%</td>\n",
       "      <td id=\"T_34cec_row9_col4\" class=\"data row9 col4\" >2.65%</td>\n",
       "      <td id=\"T_34cec_row9_col5\" class=\"data row9 col5\" >0.11%</td>\n",
       "      <td id=\"T_34cec_row9_col6\" class=\"data row9 col6\" >2.61%</td>\n",
       "      <td id=\"T_34cec_row9_col7\" class=\"data row9 col7\" >6.48%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row10\" class=\"row_heading level0 row10\" >40.500000</th>\n",
       "      <td id=\"T_34cec_row10_col0\" class=\"data row10 col0\" ></td>\n",
       "      <td id=\"T_34cec_row10_col1\" class=\"data row10 col1\" >-2.98%</td>\n",
       "      <td id=\"T_34cec_row10_col2\" class=\"data row10 col2\" >-0.86%</td>\n",
       "      <td id=\"T_34cec_row10_col3\" class=\"data row10 col3\" >0.51%</td>\n",
       "      <td id=\"T_34cec_row10_col4\" class=\"data row10 col4\" >5.46%</td>\n",
       "      <td id=\"T_34cec_row10_col5\" class=\"data row10 col5\" >1.31%</td>\n",
       "      <td id=\"T_34cec_row10_col6\" class=\"data row10 col6\" >1.74%</td>\n",
       "      <td id=\"T_34cec_row10_col7\" class=\"data row10 col7\" >9.82%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row11\" class=\"row_heading level0 row11\" >56.690000</th>\n",
       "      <td id=\"T_34cec_row11_col0\" class=\"data row11 col0\" ></td>\n",
       "      <td id=\"T_34cec_row11_col1\" class=\"data row11 col1\" >-1.37%</td>\n",
       "      <td id=\"T_34cec_row11_col2\" class=\"data row11 col2\" >-1.05%</td>\n",
       "      <td id=\"T_34cec_row11_col3\" class=\"data row11 col3\" >2.13%</td>\n",
       "      <td id=\"T_34cec_row11_col4\" class=\"data row11 col4\" >6.47%</td>\n",
       "      <td id=\"T_34cec_row11_col5\" class=\"data row11 col5\" >0.10%</td>\n",
       "      <td id=\"T_34cec_row11_col6\" class=\"data row11 col6\" >-4.11%</td>\n",
       "      <td id=\"T_34cec_row11_col7\" class=\"data row11 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row12\" class=\"row_heading level0 row12\" >79.370000</th>\n",
       "      <td id=\"T_34cec_row12_col0\" class=\"data row12 col0\" ></td>\n",
       "      <td id=\"T_34cec_row12_col1\" class=\"data row12 col1\" >-2.50%</td>\n",
       "      <td id=\"T_34cec_row12_col2\" class=\"data row12 col2\" >-3.25%</td>\n",
       "      <td id=\"T_34cec_row12_col3\" class=\"data row12 col3\" >1.75%</td>\n",
       "      <td id=\"T_34cec_row12_col4\" class=\"data row12 col4\" ></td>\n",
       "      <td id=\"T_34cec_row12_col5\" class=\"data row12 col5\" >0.41%</td>\n",
       "      <td id=\"T_34cec_row12_col6\" class=\"data row12 col6\" ></td>\n",
       "      <td id=\"T_34cec_row12_col7\" class=\"data row12 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row13\" class=\"row_heading level0 row13\" >111.120000</th>\n",
       "      <td id=\"T_34cec_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_34cec_row13_col1\" class=\"data row13 col1\" >-4.22%</td>\n",
       "      <td id=\"T_34cec_row13_col2\" class=\"data row13 col2\" >-5.06%</td>\n",
       "      <td id=\"T_34cec_row13_col3\" class=\"data row13 col3\" >-2.81%</td>\n",
       "      <td id=\"T_34cec_row13_col4\" class=\"data row13 col4\" ></td>\n",
       "      <td id=\"T_34cec_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_34cec_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "      <td id=\"T_34cec_row13_col7\" class=\"data row13 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_34cec_level0_row14\" class=\"row_heading level0 row14\" >155.570000</th>\n",
       "      <td id=\"T_34cec_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_34cec_row14_col1\" class=\"data row14 col1\" ></td>\n",
       "      <td id=\"T_34cec_row14_col2\" class=\"data row14 col2\" >-3.64%</td>\n",
       "      <td id=\"T_34cec_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_34cec_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_34cec_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_34cec_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_34cec_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2cd2c8f10>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.039789285050917056\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0124\n",
      "Universal Metric of SM2: 0.0835\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
